Books Published

Sinatra, A.M., Graesser, A.C., Hu, X., Goldberg, B., and Rus. V. (Eds). (2023). Design Recommendations for Intelligent Tutoring Systems: Volume 10 - SWOT Analysis. Orlando, FL: US Army Combat Capabilities Development Command - Soldier Center.

Rus, V. & Fancsali, S. (2022). Proceedings of The Third Workshop of the Learner Data Institute - Big Data, Research Challenges, and Science Convergence in Educational Data Science, The 15th International Conference on Educational Data Mining (EDM 2022), July 27, Durham, UK.

Sinatra, A.M., Graesser, A.C., Hu, X., Goldberg, B., and Rus. V. (Eds.). (2022). Design Recommendations for Intelligent Tutoring Systems: Volume 10 - SWOT Analysis. Orlando, FL: US Army Combat Capabilities Development Command - Soldier Center.

Rus, V. & Fancsali, S. (2021). Proceedings of The Second Workshop of the Learner Data Institute - Big Data, Research Challenges, & Science Convergence in Educational Data Science, The 14th International Conference on Educational Data Mining (EDM 2021), June 29- July 2, Paris, France (held online).

Rus, V. & Fancsali, S. (2020). Proceedings of The First Workshop of the Learner Data Institute - Big Data, Research Challenges, & Science Convergence in Educational Data Science, The 13th International Conference on Educational Data Mining (EDM 2020), July 10-13, Ifrane, Morroco (held online).

Sinatra, A.M., Graesser, A.C., Hu, X., Brawner, K., and Rus, V. (Eds.). (2019). Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Self-Improving Systems. Orlando, FL: U.S. Army Research Laboratory. ISBN 978-0-9977257-7-3.

Brawner, K., and Rus, V. (2018). Proceedings of the 31st Florida Artificial Intelligence Research Society Conference, Brawner, K. and Rus, V. (Editors), 872 pp., references, index, illus., ISBN 978-1-52735-437-2, The AAAI Press, Palo Alto, California.

Rus, V., and Markov, Z. (2017). Proceedings of the 30th Florida Artificial Intelligence Research Society Conference, Vasile Rus and Zdravko Markov (Editors), 826 pp., references, index, illus., ISBN 978-1-57735-787-2, The AAAI Press, Palo Alto, California.

Rus, V. & Graesser, A.C. (Eds.) (2009). The Question Generation Shared Task and Evaluation Challenge. ISBN: 978-0-615-27428-7.     

Rus, V. & Lester, J. (Eds.) (2009). Proceedings of the 2^nd Workshop on Question Generation. July 6, 2009, Brighton, UK. 

Forascu, C., Ionita, A., Tufis, D., Cristea, D. & Rus, V. (Eds.) (2012). Language Technologies in Romanian and Diaspora Research & Development, September 2012, University Al.I. Cuza Publishing House, Iasi, Romania. ISBN 978-973-703-813-5.

Tufis, D., Rus, V., & Forascu, C. (eds.) (2013). Towards Multilingual Europe 2020: A Romanian Perspective, Romanian Academy Publishing House, Bucharest, Romania, February 2013, ISBN 978-973-27-2282-4. 370 pp.

BOOK CHAPTERS [suggested by CS T&P to be included here]

Rus, V., Olney, A. M., & Graesser, A. C. (2023). Deeper learning through interactions with students in natural language. In B. du Boulay, A. Mitrovic, & K. Yacef (Eds.), Handbook of Artificial Intelligence in Education (pp. 250–272). Edward Elgar Publishing.

Rus, V. (2022). Domain Modelling – A S.W.O.T. Analysis. In Design Recommendations for Intelligent Tutoring Systems: Volume 10 - SWOT Analysis, Sinatra, A.M., Graesser, A.C., Hu, X., Goldberg, B., and Rus. V. (Eds.), Orlando, FL: US Army Combat Capabilities Development Command - Soldier Center.

Rus, V., Swiecki, Z., Cockroft, J.L., & Hu, X. (2020). Visualization of Sequential Interactions in Adaptive Instructional Systems, Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Visualizations. Orlando, FL: U.S. Army Research Laboratory.

Kay, J., Zapata-Rivera, D., Rus, V., Durlach, P., & Hampton, A. (2020). Open Learner Model Visualizations for contexts where learners thinks fast or slow, Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Visualizations. Orlando, FL: U.S. Army Research Laboratory.

Rus, V., Swiecki, Z., Cockroft, J. L., & Hu, X. (2020). Visualizations of sequential interactions in adaptive instructional systems, Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Visualizations. Orlando, FL: U.S. Army Research Laboratory.

Swiecki, Z., Ruis, A.R., Gautam, D., Rus, V., Shaffer, D.W. (2019). Understanding when students are active-in-thinking through modeling-in-context. BJET 50(5): 2346-2364 (2019).

Liu, M, Rus, V & Liu, L 2018, Automatic Chinese Multiple Choice Question Generation Using Mixed Similarity Strategy, IEEE Transactions on Learning Technologies, vol. 11, no. 2, pp. 193-202.

Liu, M, Rus, V, Li, Y, Sheng, C & Liu, L 2018, Automatic Chinese character similarity measurement, Web Intelligence, vol. 16, no. 3, pp. 195-202.

Graesser, A.C., McNamara, D., & Rus, V. (2018). Computational Modeling of Discourse and Conversation, Cambridge Handbook of Psycholinguistics, edited by Michael Spivey, Marc Joanisse, and Ken McRae.

Graesser, A.C., Hu, X., Rus, V., & Cai, Z. (2018). AutoTutor and other Conversationbased Learning and Assessment Environments, Chapter for Handbook of Automated Scoring: Theory into Practice, edited by Andre Rupp, Duanli Yan, and Peter Foltz

Dede, C., Grotzer, T.A., Kamarainen, A., Metcalf, S., Olney, A., Rus, V., Sottilare, R.A., & Wang, M. (2018). Graphical supports for collaboration: Constructing shared mental models. In Sottilare, R., Graesser, A.C., Hu, X. et al. (Eds.), Design Recommendations for Intelligent Tutoring Systems, v. 6 Team Tutoring, p. 33-43. Orlando, FL: US Army Research Laboratory (ARL), 2018.

Graesser, A.C., Hu, X., Nye, B., VanLehn K., Kumar, R., Heffernan, C., Heffernan, N., Woolf, B., Olney, A.M., Rus, V., Andrasik, F., Pavlik, P., Cai, Z., Wetzel, J., Morgan, B., Hampton, A.J., Lippert, A.M., Wang, L., Chen, Q., Vinson IV, J.E., Kelly, C.N., McGlown, C., Majmudar, C.A., Morshed, B., and Baer, W. ElectronixTutor: an intelligent tutoring system with multiple learning resources for electronics. In International Journal of STEM Education: Innovations and Research, January 2017. DOI 10.1186/s40594-017-0072-5.

Graesser, A.C., Rus, V., Hu, X. (2017). Instruction based on tutoring. In R.E. Mayer and P.A. Alexander (Eds.), Handbook of Research on Learning and Instruction (2nd edition, 2017). New York: Routledge Press.

Liu, M., Rus, V., & Liu, L. (2018). Automatic Chinese Multiple Choice Question Generation Using Mixed Similarity Strategy, IEEE’s Transactions on Learning Technologies.

Rus. V. & Stefanescu, D. (2016). Non-intrusive assessment of learners’ prior knowledge in dialogue-based intelligent tutoring systems. Journal of Smart Learning Environments. (2016) 3:2, pp. 1-18. Springer International.

Rus, V., Maharjan, N., & Banjade, R. (2015). Unsupervised Discovery of Tutorial Dialogue Modes in Human-to-Human Tutorial Data, Proceedings of the Third Annual GIFT Users Symposium (Eds. Sottilare, R. and Sinatra, A.M.), Army Research Lab, June 2015, pp. 63-80.

Rus, V., Conley, M., & Graesser, A. (2014). The DENDROGRAM Model of Instruction: On Instructional Strategies and Their Implementation in DeepTutor, Design Recommendations for Adaptive Intelligent Tutoring Systems: Adaptive Instructional Strategies (Volume 2), (Eds. Sottilare, R.), Army Research Lab.

Ming, L., Calvo, R., & Rus, V. (2014). Automatic Generation and Ranking of Questions for Critical Review, Journal of Educational Technology Society Journal, v14 - N 3. pp. 16-27.

Rus, V., D’Mello, S., Hu, X., & Graesser, A.C. (2013). Recent Advances in Conversational Intelligent Tutoring Systems, AI Magazine, 34(3):42-54.

Rus, V., Baggett, W., Gire, E., Franceschetti, D., Conley, M., Graesser, A.C. (2013). Towards Learner Models based on Learning Progressions in DeepTutor, Learner Models (Eds. Sottilare, R.), Army Research Lab.

Ming, L.. and Rus, V. (under review). Automatic Neural Chinese Question Generation, ACM’s Transactions on Learning Technologies

Rus, V., Olney, A.M., Foltz, P., Hu, X. (2017). Automated Assessment of Learner-Generated Natural Language Responses, In R. Sottilare, A. Graesser, X. Hu, & G. Goodwin (Eds.), Design Recommendations for Intelligent Tutoring Systems: Assessment Methods (Vol. 5, pp. 155–170). Orlando, FL: U.S. Army Research Laboratory.

Carlin, A., Rus, V., & Nye, B. (2018). Bayesian Model of Team Training and Measures, In Sottilare, R., Graesser, A.C., Hu, X. et al. (Eds.), Design Recommendations for Intelligent Tutoring Systems, v. 6 Team Tutoring, p. 33-43. Orlando, FL: US Army Research Laboratory (ARL), 2018.

Rus, V., Conley, M., & Graesser, A. (2014). The DENDROGRAM Model of Instruction: On Instructional Strategies and Their Implementation in DeepTutor, Design Recommendations for Adaptive Intelligent Tutoring Systems: Adaptive Instructional Strategies (Volume 2), (Eds. Sottilare, R.), Army Research Lab.

McNamara, D., Raine, R., Roscoe, R., Crossley, S., Dai, J., Cai, Z., Renner, A., Brandon, R., Weston, J., Dempsey, K., Lam, D., Sullivan, S., Kim, L., Rus, V., Floyd, R., McCarthy, P., & Graesser, A. (2012). The Writing Pal: natural language algorithms to support intelligent tutoring on writing strategies. In P. McCarthy & C. Boonthum (eds.), Applied natural language processing and content analysis: identification, investigation, and resolution. Hershey, PA: IGI Global.

Rus, V., Linean, M., Cai, Z., Graesser, A.C., Witherspoon, A., & Azevedo, R. (2011). Computational Aspects of The Intelligent Tutoring System MetaTutor, In Applied Natural Language Processing, Phillip McCarthy and Chutima Boonthum-Denecke (Eds.), IGI Global, 2011.

Rus, V., Lintean, M., Graesser, A.C, & McNamara, D.S. (2011). Text-to-Text Similarity of Sentences, In Applied Natural Language Processing, Phillip McCarthy and Chutima Boonthum-Denecke (Eds.), IGI Global, 2011.

Graesser, A.C., Rus, V., Cai, Z., & Hu, X. (2011). Question Answering and Generation, In Applied Natural Language Processing, Phillip McCarthy and Chutima Boonthum-Denecke (Eds.), IGI Global, 2011.

Rus. V. (2010). Challenges and Solutins in Intelligent Tutoring Systems with Natural Language Interaction, in Forascu, C. & Tufis, D.,  Multilinguality and Interoperability in Language Processing, Romanian Academy Press, ISBN: 978-973-27-1972-5.

Arthur C. Graesser, Vasile Rus, Sidney D’Mello, & Tanner G. Jackson. (2008). AutoTutor: Learning through natural language dialogue that adapts to the cognitive and affective states of the learner. In D. H. Robinson & G. Schraw (Eds.), Current perspectives on cognition, learning and instruction: Recent innovations in educational technology that facilitate student learning (pp. 95–125). Information Age Publishing. [invited book chapter]  

Vasile Rus, Philip McCarthy, Danielle McNamara, and Arthur C. Graesser. (2008). Natural Language Understanding and Assessment, Chapter in Encyclopedia of Artificial Intelligence, ISBN: 978-1-59904-849-9, July, 2008 [invited book chapter]

Philip McCarthy, Stephen Briner, Vasile Rus, and Danielle McNamara, Textual signatures: Identifying text-types using Latent Semantic Analysis to measure the cohesion of text structures. In: A. Kao, & S. Poteet (Eds.). Natural Language Processing and Text Mining (pp. 107-122). London: Springer-Verlag UK. 2007. [Book Chapter; 5% acceptance rate] 

Arthur C. Graesser, Danielle S. McNamara, and Vasile Rus, Computational modeling of discourse and conversation. In M. Spivey, M. Joanisse, & K. McRae (Eds.), Cambridge Handbook of Psycholinguistics: Cambridge: Cambridge University Press. 2007. [invited Book Chapter]

Vasile Rus and Arthur C. Graesser, Lexico-Syntactic Subsumption for Textual Entailment, In Recent Advances in Natural Language Processing, John Benjamins Publishing Company, 2007 [invited Book Chapter; invitation based on selection of papers from the accepted papers at the International Conference on Recent Advances in Natural Language Processing 2005; 4% selection rate]    

Refereed Journal Publications

Rus, V., Tamang, L, Oli, P., Banjade, R., Brusilovsky, P. (submitted) DeepCode: An Annotated Instructional CodeSet Based on Code Comprehension and Learning Theories To Foster The Development of Code Comprehension Adaptive Instructional Systems, ACM Transactions on Learning Engineering.

Rus. V. & Stefanescu, D. (2016). Non-intrusive assessment of learners' prior knowledge in dialogue-based intelligent tutoring systems. Journal of Smart Learning Environments. (2016) 3:2, pp. 1-18. Springer International.

Graesser, A.C., Rus, V., & Hu, X. (in press). Instruction based on tutoring.  In R.E. Mayer & P.A. Alexander (Eds.), Handbook of Research on Learning and Instruction.

Rus. V. & Stefanescu, D. (in press). Non-intrusive assessment of learners’ prior knowledge in dialogue-based intelligent tutoring systems. Journal of Smart Learning Environments. (in press) Springer International.

Impact Factor and/or Acceptance Rates reported when available.

Citations are available on Google Scholar: http://scholar.google.com/citations?user=k8jqnc8AAAAJ&hl=en [also included in Supplemental Materials section of the dossier]

Ming, L., Calvo, R., & Rus, V. (2014). Automatic Generation and Ranking of Questions for Critical Review, Journal of Educational Technology Society Journal, 17(2), 333-346. [impact factor: 0.824]

Rus, V., D'Mello, S., Hu, X., & Graesser, A.C. (2013). Recent Advances in Conversational Intelligent Tutoring Systems, AI Magazine, 34 (3), 2013. [impact factor: 0.73]

 Rus, V., Wyse, B., Piwek, P., Lintean, M., Stoyanchev, S., & Moldovan, C. (2012). A Detailed Account of The First Question Generation Shared Task Evaluation Challenge, Special Issue on Question Generation of the Journal of Dialogue and Discourse, Vol. 3., No. 2, pp. 177-204. [acceptance rate - 17%]

Lintean, M., Rus, V., & Azevedo, R. (2011). Automatic Detection of Student Mental Models during Prior Knowledge Activation in MetaTutor, International Journal of Artificial Intelligence in Education, 21(3), pp. 169-190. [acceptance rate: 23%]

Ming, L. Calvo, R., & Rus, V. (2012). G-Asks: An Intelligent Automatic Generation System for Academic Writing Support, Special Issue on Question Generation of the Journal of Dialogue and Discourse, Vol. 3., No. 2, pp. 101-124. [acceptance rate - 17%]

Shala, L., Rus, V. & Graesser, A. (2010). Automatic Speech Act Classification in Arabic. Subjetividad y Procesos Cognitivos Journal, Vol. 14, No. 2, 2010, pp. 284-292. [acceptance rate - 13%]

Lintean, M., & Rus, V. (2010). Paraphrase Identification Using Weighted Dependencies and Lexical Semantics. Informatica: The International Journal of Computing. 34(2010), 19-28. [acceptance rate - 16%]

Vasile Rus, Philip M. McCarthy, Arthur C. Graesser, & Danielle S. McNamara. (2009). Identification of Sentence-to-Sentence Relations Using a Textual Entailer, International Journal on Research in Language and Computation, 7(2-4), 209-229.

Vasile Rus, Ingrid Russell, & Zdravko Markov. (2009), MLxAI: Biomedical Term Classification, The Journal of Computing Sciences in Colleges, 24(5), pages 85-92. [acceptance rate – 42%]

Vasile Rus, Philip McCarthy, Danielle McNamara, and Arthur C. Graesser. (2008). A Study on Textual Entailment, International Journal on Artificial Intelligence Tools, 17(4):659-685-499, August, 2008 [acceptance rate - 13%]

Mihai Lintean and Vasile Rus, Large Scale Experiments with Naïve Bayes and Decision Trees for Function Tagging, International Journal on Artificial Intelligence Tools, 17(3):483-499, June, 2008 [acceptance rate - 13%] 

Vasile Rus and Arthur C. Graesser, Lexico-Syntactic Subsumption for Textual Entailment, In Recent Advances in Natural Language Processing, John Benjamins Publishing Company, 2007 [invited Book Chapter; invitation based on selection of papers from the accepted papers at the International Conference on Recent Advances in Natural Language Processing 2005; 4% selection rate]    

Christian H. Hempelmann, Vasile Rus, Arthur C. Graesser, and Danielle S. McNamara, “Evaluating State-of-the-Art Treebank-style Parsers for Coh-Metrix and Other Learning Technology Environments”,  Natural Language Engineering, 12-2, 2006, Pages 131-144. [18% acceptance rate]  

Vasile Rus and Sireesha Ravi, “Towards a Base Noun Phrase Parser Using Web Counts”, Journal of Computing Sciences in Colleges, Volume 21, 2006, Issue 5, Pages 162-169. [46% acceptance rate]    

Vasile Rus and Christian Hempelmann, “Across-Genres and Empirical Evaluation of State-of-the-Art”, Treebank-style Parsers, International Journal of Archives of Control Sciences, Special Issue,Volume 15(LI), October 2005, No. 3, Pages 251-261.  [12% acceptance rate]  

James Markham, Vasile Rus: On the implementation of a baseline part-of-speech tagger , Journal of Computing Sciences in Colleges, Volume 20,  Issue 6  (June 2005), Pages 151 - 159. [46% acceptance rate]   

Vasile Rus : “Automated Learning Applied to Functional Arguments Identification”, International Journal of Computing and Information Technologies, Vol. 12, No. 3, September 2004, Pages 211-223. [18% acceptance rate]    

Vasile Rus and Dan I. Moldovan: High Precision Logic Form Transformation, International Journal on Artificial Intelligence Tools, vol. 11 no. 3, September 2002, Pages 437-455. [13% acceptance rate]  

Refereed Conference Publications

Lekshmi-Narayanan, A.B., Oli, P., Chapagain, J., Hassany, M., Banjade, R., Brusilovsky, P., & Rus, V. (2024). Explaining Code Examples in Introductory Programming Courses: LLM vs Humans, In Proceedings of the AI for Education Workshop, AAAI 2024, Vancouver, Canada.

Oli, P., Banjade, R., Chapagain, J., Rus, V. (2024). Automated Assessment of Students' Code Comprehension using LLMs, Proceedings of the AI for Education Workshop, AAAI 2024, Vancouver, Canada

Oli, P., Banjade, R., Lekshmi-Narayanan, A.B., Brusilovsky, P., and Rus, V. (2024). Exploring The Effectiveness of Reading vs. Tutoring For, Enhancing Code Comprehension For Novices. In Proceedings of ACM SAC Conference (SAC'24). ACM, Avila, Spain

Banjade, R. & Oli, P. & Sajib, M.H, & Rus, V. (2024). Identifying Gaps in Students’ Explanations of Code Using LLMs. Proceedings of The 25^th International Conference on Artificial Intelligence in Education ; AIED 2024. 8-12 July; Recife, Brazil, 10.1007/978-3-031-64299-9_21.

Shakya, A., Rus, V. and Venugopal, D. (2023). Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. Proceedings of the 16th International Conference on Educational Data Mining, 137—148, Bengaluru, India, July, 2023, https://doi.org/10.5281/zenodo.8115669.

Banjade, R. & Oli, P. & Rus, V. (2023). Automated Extraction of Domain Models from Textbook Indexes for Developing Intelligent Tutoring Systems. In Augmented Intelligence and Intelligent Tutoring Systems: 19th International Conference, ITS 2023, Corfu, Greece, June 2–5, 2023, Proceedings. Springer-Verlag, Berlin, Heidelberg,  https://doi.org/10.1007/978-3-031-32883-1_11.

Oli, P., Banjade, R., Chapagain, J., & Rus, V. (2023). The Behavior of Large Language Models When Prompted to Generate Code Explanations.  Proceedings of The workshop on Generative AI for Education (GAIED): Advances, Opportunities, and Challenges, The Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, December 2023.

Oli, P., Banjade, R., Lekshmi-Narayanan, A.B., Chapagain, J., Tamang, L.J., Brusilovsky, P., and & Rus. V. Improving code comprehension through scaffolded self-explanations. In International Conference on Artificial Intelligence in Education, pages 478–483. Springer, 2023.

Chapagain, J., Risha, Z., Banjade, R., Oli, P., Tamang, L., Brusilovsky, P., & Rus, V. (2023). SelfCode: An Annotated Corpus and a Model for Automated Assessment of Self-Explanation During Source Code Comprehension. The International FLAIRS Conference Proceedings, 36(1). https://doi.org/10.32473/flairs.36.133385.

Chapagain, J., Tamang, L., Banjade, R., Oli, P., & Rus, V. (2022). Automated Assessment of Student Self-explanation During Source Code Comprehension. The International FLAIRS Conference Proceedings, 35.

Rus, V., Fancsali, S.E., Pavlik Jr., P., Venugopal, D., Bowman, D., Ritter, and The LDI Team. (2022). The Learner Data Institute: Emerging Science Convergence and Research Opportunities, Proceedings of The Third Workshop of the Learner Data Institute , The 15th International Conference on Educational Data Mining (EDM 2022), July 27, Durham, UK.

Rus, V., Akhuseyinoglu, K., Chapagain, J., Tamang, L.J. (2021, June). Prompting for Free Self-Explanations Promotes Better Code Comprehension. In 5th Educational Data Mining in Computer Science Education (CSEDM) Workshop in Conjunction with The 14th International Educational Data Mining Conference (EDM 2021), June 29 – July 2, Paris, France (held online)

Oli, P., Banjade, R., Tamang, L. J., & Rus, V. (2021). Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code. In Proceedings of the 34th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2021), Miami, FL, USA May 17-20, 2021.

Tamang, L. J., Alshaikh, Z., Khayi, N. A., Oli, P., & Rus, V. (2021, March). A Comparative Study of Free Self-Explanations and Socratic Tutoring Explanations for Source Code Comprehension. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 219-225).

Alshaikh, Z., Tamang, L. J., & Rus, V. (2021). Experiments with Auto-generated Socratic Dialogue for Source Code Understanding. In CSEDU (2) (pp. 35-44).

Ait Khayi, N., & Rus, V. & Tamang, L (2021). Towards Improving Student Answers Assessment using Pretrained Transformers. In Proceedings of the 34th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2021), Miami, FL, USA May 17-20, 2021.

Ait Khayi, N., & Rus, V. & Tamang, L (2021). Deep Knowledge Tracing using Temporal Convolutional Networks. AI4EDU@IJCAI.

Banjade, R., Oli, P., Tamang, L. J., Chapagain, J., & Rus, V. (2021). Domain Model Discovery from Textbooks for Computer Programming Intelligent Tutors. In Proceedings of the 34th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2021), Miami, FL, USA May 17-20, 2021.

Rus, V.. (2021). The Learner Data Institute—Conceptualization: A Progress Report. Proceedings of the 2nd Learner Data Institute Workshop in Conjunction with The 14th International Educational Data Mining Conference (EDM 2021), June 29 – July 2, Paris, France (held online).

Banjade, R., Niraula, N., and Rus, V. (2016). Towards Intra- and Inter-Sentential Negation Scope and Focus Detection in Tutorial Dialogue. Proceedings of the Twenty-Nineth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2016), Key Largo Resort, Key Largo, Florida, USA May 16-18, 2016.

Banjade, R., Maharjan, N., Niraula, N.B., and Rus, V. (2016). DT-Sim at Semeval-2016 task 2: Interpretable semantic textual similarity. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), San Diego, California, June. Association for Computational Linguistics.

Banjade, R., Maharjan, N., Gautam, D., and Rus, V. (2016). DTSim at SemEval-2016 Task 1: Semantic Similarity Model Including Multi-Level Alignment and Vector-Based Compositional Semantics, In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), The 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies will be held in San Diego, California, June 12 to June 17, 2016.

Rus, V., Banjade, R., Maharjan, N., Morrison, D., Ritter, S., and Yudelson, M. (2016). Preliminary Results on Dialogue Act Classification in Chatbased Online Tutorial Dialogues, Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, NC, June 29 - July 2, 2016.

Venugopal, D. and Rus, V. (2016). Joint Inference for Mode Identification in Tutorial Dialogues, Proceedings of the 26th International Conference on Computational Linguistics (COLING 2016), Osaka, Japan, December 11-16, 2016

Rus, V., Banjade, R., Niraula, N., Gire, E., Franceschetti, D. (2016). The 3rd International Conference On Smart Learning Environments, Lecture Notes in Educational Technology, pp. 171-181, Springer, 2016.

Banjade, R., Maharjan, N., Niraula, N.B., Gautam, D., Samei, B., and Rus, V. (2016). Evaluation Dataset (DT-Grade) and Word Weighting Approach towards Constructed Short Answers Assessment in Tutorial Dialogue Context, The 11th Workshop on Innovative Use of NLP for Building Educational Applications (NAACL 2016), The 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies will be held in San Diego, California, June 12 to June 17, 2016.

Rus, V., Gautam, D., Swiecki, Z., Shaffer, D.W., Graesser, A.C. (2016). Assessing Student-Generated Design Justifications in Engineering Virtual Internships, Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, NC, June 29 - July 2, 2016.

Fancsali, S.E., Ritter, S., Berman, S.R., Yudelson, M., Rus, V., and Morrison, D.M. (2016). Toward Integrating Cognitive Tutor Interaction Data with Human Tutoring Text Dialogue Data in LearnSphere, Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, NC, June 29 - July 2, 2016.

Ritter, S., Fancsali, S.E., Yudelson, M., Rus. V., and Berman, S. (2016). Toward Intelligent Instructional Handoffs Between Humans and Machines, 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, December 5-10, 2016.

Rus, V. & Stefanescu, D. (2015). Towards Non-Intrusive Assessment in Dialogue-based Intelligent Tutoring Systems, The 2nd International Conference on Smart Learning Environments, September 23-25, Sinaia, Romania. [BEST PAPER AWARD]

Banjade, R., Niraula, N., Maharjan, N., Rus, V., Stefanescu, D., Lintean, M., & Gautam, D. (2015). NeRoSim: A System for Measuring and Interpreting Semantic Textual Similarity, Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 164–171, Denver, Colorado, June 4-5, 2015. [WINNER OF SEMEVAL COMPETITION]

Rus, V., Niraula, N., Maharjan, N., & Banjade, R. (2015). Automated Labelling of Dialogue Modes in Tutorial Dialogues, Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2015, May 18-20, 2015, Hollywood, Florida, AAAI Press 2015.

Niraula, N., Gautam, D., Banjade, R., Maharjan, N., Rus, V. (2015). Combining Word Representations for Measuring Word Relatedness and Similarity, Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2015, May 18-20, 2015, Hollywood, Florida, AAAI Press 2015.

Banjade, R., Rus, V., Niraula, N. (2015). Using an Implicit Method for Coreference Resolution and Ellipsis Handling in Automatic Student Answer Assessment, Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2015, May 18-20, 2015, Hollywood, Florida, AAAI Press 2015.

Niraula, N., & Rus, V. (2015). Judging the Quality of Automatically Generated Gap-fill Question using Active Learning, Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications, 2015, pages 196–206, Denver, Colorado, June 4, 2015.

Lintean, M. & Rus, V. (2015). An Optimal Quadratic Approach to Monolingual Paraphrase Alignment, The 20th Nordic Conference on Computational Linguistics (NODALIDA 2015), Lithuania, Vilnius, 11 - 13 May 2015.

Banjade, R., Maharjan, N., Niraula, N., Rus, V., & Gautam, D. (2015). Lemon and Tea Are Not Similar: Measuring Word-to-Word Similarity by Combining Different Methods, Computational Linguistics and Intelligent Text Processing, Lecture Notes in Computer Science, Volume 9041, 2015, pp 335-346.

Rus, V., Niraula, N., & Banjade, R. (2015). DeepTutor: An Effective, Online Intelligent Tutoring System That Promotes Deep Learning, The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15). January 25–30, 2015, Austin, Texas, USA.

Samei, B., Rus, V., Nye, B., & Morrison, D. (2015). Hierarchical Dialogue Act Classification in Online Tutoring Sessions, The Eighth International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. June 26-29, 2015.

Rus, V., Graesser, A., Niraula, N., & Banjade, R. (2015). DeepTutor: Integrating Learning Progressions In Unsupervised After-school Online Intelligent Tutoring, The 17th International Conference on Artificial Intelligence in Education (AIED 2015), June 22-26, 2015, Madrid, Spain.

Rus, V., Maharjan, N., & Banjade, R. (2015). Unsupervised Discovery of Tutorial Dialogue Modes in Human-to-Human Tutorial Data, The 3^rd Generalized Intelligent Tutoring Framework Symposium, June 17-18, Orlando, FL.

Niraula, N. & Rus, V. (2014). A Machine Learning Approach to Anaphora Resolution in Dialogue based Intelligent Tutoring Systems, In Proceedings of 15th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2014), April 6-12, Kathmandu, Nepal. [acceptance rate - 23%]

Niraula, N. & Rus, V. (2014). Mining Gap-fill Questions from Tutorial Dialogues, The 7th International Conference on Educational Data Mining. EDM 2014. July 4, 2014.

Brent, M., Baggett, W.B., Graesser, A.C., & Rus, V.. (2014). Error Analysis As A Validation of Learning Progressions, The 7th International Conference on Educational Data Mining. EDM 2014. July 4, 2014.

Stefanescu, D., Graesser, A.C., & Rus, V. (2014). Assessing Students’ Prior Knowledge From Tutorial Dialogues, The 7th International Conference on Educational Data Mining. EDM 2014. July 4, 2014.

Samei, B., Li, H., Rus, V., & Graesser, A.C. (2014). Context-based Speech Act Classification in Intelligent Tutoring Systems, The 12^th International Conference on Intelligent Tutoring Systems, June 5-9, Honolulu, Hawaii.

Rus, V., Stefanescu, D., Baggett, W., Niraula, N., Franceschetti, D., & Graesser, A.C. (2014). Macro-adaptation in Conversational Intelligent Tutoring Matters, The 12^th International Conference on Intelligent Tutoring Systems, June 5-9, Honolulu, Hawaii.[acceptance rate - 17.5%]

Shala, L., Rus., V. & Graesser, A.C. (2014). A Bilingual Analysis of Cohesion in a Corpus of Leader Speeches, The 27th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2014), May 21-23, Pensacola Beach, FL, USA. [acceptance rate - 44%]

Rus, V. (2014). Opportunities and Challenges in Semantic Similarity, The 27th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2014), Invited Paper (based on the Invited Talk I gave), May 21-23, Pensacola Beach, FL, USA.

Rus, V., Banjade, R., and Lintean, M. (2014). On Paraphrase Identification Corpora, The 9^th International Conference on Language Resources and Evaluation, Reykjavik, May 26-31, 2014, Iceland. [acceptance rate - 57%]

Niraula, N., Rus, V., Banjade, R., Stefanescu, D., Baggett, W. and Morgan, B. (2014). The DARE Corpus: A Resource for Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems, The 9^th International Conference on Language Resources and Evaluation, Reykjavik, May 26-31, 2014, Iceland. [acceptance rate - 57%]

Rus, V., Stefanescu, D., Niraula, N., Graesser, A.C. (2014). DeepTutor: Towards Macro- and Micro-Adaptive Conversational Intelligent Tutoring at Scale, ACM’s Learning@Scale Conference, March 4-6, 2014, Atlanta, Georgia. [acceptance rate - 37%]

Stefãnescu, D., Banjade, R., Rus, V. (2014). Latent Semantic Analysis Models on Wikipedia and TASA. The 9^th International Conference on Language Resources and Evaluation, May 26-31, 2014, Reykjavik, Iceland. [acceptance rate - 57%]

Stefãnescu, D., Rus, V., Niraula, N., Banjade, R. (2014). Combining Knowledge and Corpus-based Measures for Word-to-Word Similarity. In The 27th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2014), May 21-23, Pensacola Beach, FL, USA. [acceptance rate - 36%]

Stefãnescu, D., Banjade, R., Rus, V. (2014). A Sentence Similarity Method based on Parsing and Information Content. In Proceedings of 15th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2014), April 6-12, Kathmandu, Nepal. [acceptance rate - 23%]

Rus, V., Niraula, N., & Banjade, R. (2013). Similarity Measures based on Latent Dirichlet Allocation. The 14th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2013), March 24-30, Samos, Greece. [acceptance rate - 26%]

Rus, V., Lintean, M., Banjade, R., Niraula, N., & Stefanescu, D. (2013). SEMILAR: The Semantic Similarity Toolkit. The 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), August 4-9, Sofia, Bulgaria. [acceptance rate - 26%]

Rus, V., Niraula, N., Lintean, M., Banjade, R., Stefanescu, D., & Baggett, W. (2013). Recommendations for the Generalized Intelligent Framework for Tutoring based on the Development of the DeepTutor Tutoring Service, Workshop on Generalized Intelligent Framework for Tutoring (GIFT), The 16th International Conference on Artificial Intelligence in Education (AIED 2013), July 9-13, Memphis, TN.

Rus, V., Niraula, N., Banjade, R. (2013). A Study of Probabilistic and Algebraic Methods for Semantic Similarity, The 26th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2013), May 22-24, 2013, St. Pete Beach, FL, USA. [acceptance rate - 52%]

Morrison, D. M. & Rus, V. (2013). The SCHOLAR Legacy: A New Look at the Affordances of Semantic Networks for Conversational Agents, Workshop on Generalized Intelligent Framework for Tutoring (GIFT), The 16th International Conference on Artificial Intelligence in Education (AIED 2013), July 9-13, Memphis, TN.

Niraula, N., Rus, V., & Stefanescu, D. (2013). DARE: Deep Anaphora Resolution Engine. The 6th International Conference on Educational Data Mining (EDM 2013), July 6-9, Memphis, TN. [short paper acceptance rate - 45%]

Rus, V., Banjade, R., Lintean, M., Niraula, N., & Stefanescu, D. (2013). SEMILAR: A Semantic Similarity Toolkit for Assessing Students' Natural Language Inputs, The 6th International Conference on Educational Data Mining (EDM 2013), July 6-9, Memphis, TN. [demo paper acceptance rate - 45%]

Samei, B., Feshktar, F., Rus, V., Graesser, A.C. (2013). A Tool For Speech Act Classification Using Interactive Machine Learning, The 6th International Conference on Educational Data Mining (EDM 2013), July 6-9, Memphis, TN. [demo paper acceptance rate - 45%]

Niraula, N., Banjade, R., Stefanescu, D., Rus, V. (2013). Experiments with Semantic Similarity Measures based on LDA and LSA. The 1st International Conference on Statistical Speech and Language Processing (SLSP 2013), July 29-31, Tarragona, Spain. [acceptance rate - 29%]

Rus, V., Banjade, R., Niraula, N., & Stefanescu, D. (2013). Latent Concepts versus Latent Topics. In Proceedings of The 23rd Meeting of The Society for Text and Discourse, July 16-18, Valencia, Spain.

Rus, V., Lintean, M. (2012). “A Comparison of Greedy and Optimal Assessment of Natural Language Student Input Using Word-to-Word Similarity Metrics”, Proceedings of the Seventh Workshop on Building Educational Applications Using NLP, The 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, June, 2012, Montreal, Canada. [acceptance rate - 23%]

Rus, V., Lintean,  M., Moldovan, C., Baggett, W., Niraula, N., Morgan, B. (2012). The SIMILAR Corpus: A Resource to Foster the Qualitative Understanding of Semantic Similarity of Texts, In Semantic Relations II: Enhancing Resources and Applications, The 8th Language Resources and Evaluation Conference (LREC 2012), May 23-25, Instanbul, Turkey. [acceptance rate - 62%]

Lintean, M. & Rus, V. (2012). Measuring Semantic Similarity in Short Texts through Greedy Pairing and Word Semantics. Proceedings of the 25th International Florida Artificial Intelligence Research Society Conference. Marco Island, FL. [acceptance rate - 49%]

Rus, V., Graesser, A., Moldovan, C., & Niraula, N. (2012). "Automatic Discovery of Speech Act Categories in Educational Games", 5th International Conference on Educational Data Mining (EDM12), June 19-21, Chania, Greece. [acceptance rate - 32%]

Bhattarai, A., Niraula, N., Rus, V., Lin, K. (2012). "A Domain Independent Framework to Extract and Aggregate Analogous Features in Reviews", Cicling 2012, March 11-17, IIT Delhi, India. [acceptance rate - 28%]

Liu, M., Calvo, R.A., & Rus, V. (2012). Hybrid Question Generation Approach for Critical Review Writing Support. G. Biswas et al. (Eds.) (2012). Proceedings of the 20th International Conference on Computers in Education. Singapore: Asia-Pacific Society for Computers in Education. [acceptance rate - 34%]

 Rus, V., Wyse, B., Lintean, M., Piwek, P., Stoyanchev, S., Moldovan, C. (2011). Question Generation Shared Task and Evaluation Challenge – Status Report, Proceedings of the 13^th European Workshop on Natural Language Generation (ENLG), Nancy, France, September 2011. [acceptance rate - 30%]

Rus, V., Moldovan, C., Witherspoon, A., & Graesser, A.C. (2011). Automatic Identification of Speakers’ Intentions in A Multi-Party Dialogue System, International Conference of the Society for Text and Discourse, Poitier, France, July 2011.

Lintean, M., & Rus, V. (2011). Dissimilarity Kernels for Paraphrase Identification, Proceedings of the 24th International Florida Artificial Intelligence Research Society Conference, Palm Beach, FL, May, 2011. [acceptance rate - 47%]

Rus, V., Feng, S., Brandon, R., Crossley, S., & McNamara, D.S. (2011). A Linguistic Analysis of Student Generated Paraphrases, Proceedings of the 24^th International Florida Artificial Intelligence Research Society Conference, Palm Beach, FL, May, 2011. [acceptance rate - 47%]

Moldovan, C., Rus, V., & Graesser, A.C. (2011). Automated Speech Act Classification for Online Chat, The 22^nd Midwest Artificial Intelligence and Cognitive Science Conference, Cincinatti, OH, April 2011 (Best Student Paper Award – Honorary Mention).

Rus, V., Shala, L., Graesser, A.C., Cai, Z., & Kaltner, J. (2010). Analysis of Leaders' Language and Discourse. International Conference of the Society for Text and Discourse, Chicago, IL, August 2010.

Lintean, M., Moldovan, C., Rus, V., & McNamara, D. (2010). The Role of Local and Global Weighting in Assessing The Semantic Similarity Of Texts using Latent Semantic Analysis. Proceedings of the 23st International Florida Artificial Intelligence Research Society Conference. Daytona Beach, FL. [acceptance rate - 42%]

Liu, M., Calvo, R.A., Rus, V. (2010). Automatic Question Generation for Literature Review Writing Support, Intelligent Tutoring Systems (1) 2010: 45-54. [acceptance rate - 21%]

Shala, L., Rus, V., & Graesser, A. (2010). Speech Act Classification in Arabic. Georgetown University Round Table (GURT 2010), Georgetown, D.C., March 2010.

Shala, L., Rus, V. & Graesser, A. (2010). Automatic Speech Act Classification in Arabic. Workshop on Natural Language Processing in Social Sciences, Buenos Aires, Argentina, May 2010.

Rus, V., Shala, L., Graesser, A.C., Cai, Z., & Kaltner, J. (2010). Analysis of Leaders' Language and Discourse. To appear in International Conference of the Society for Text and Discourse, Chicago, IL, August 2010.

Rus, V., Lintean, M., & Azevedo, R., (2010). Computational Aspects of The Intelligent Tutoring System MetaTutor. Proceedings of the 23st International Florida Artificial Intelligence Research Society Conference. Daytona Beach, FL. [acceptance rate - 42%]

Rus, V., Wyse, B., Piwek, P., Lintean, M., Stoyanchev, S., & Moldovan, C. (2010). Overview of The First Question Generation Shared Task and Evaluation Challenge, In Proceedings of The 3^rd Question Generation Workshop, Pittsburgh, PA, June, 2010. [acceptance rate - 38%]

Rus, V., Wyse, B., Piwek, P., Lintean, M., Stoyanchev, S., & Moldovan, C. (2010). The First Question Generation Shared Task and Evaluation Challenge, In Proceedings of The International Natural Language Generation Conference, Dublin, Ireland, July, 2010. [acceptance rate - 35%]

Vasile Rus, Eric Woolley, Mihai Lintean, andArthur Graesser. (2009). Building Resources for an Open Task on Question Generation, Proceedings of the 2^nd Workshop on Question Generation, July 6, 2009, Brighton, UK. [invited]

Vasile Rus, Xiaofei Nan, Sajjan Shiva, & Yixin Chen. (2009). Clustering of Defect Reports Using Graph Partitioning Algorithms, Proceedings of the 20^th International Conference on Software and Knowledge Engineering, July 2-4, 2009, Boston, MA  [acceptance rate 38%]

Vasile Rus, Mihai Lintean, & Roger Azevedo. (2009). Automatic Detection of Student Mental Models During Prior Knowledge Activation in MetaTutor, Proceedings of the 2^nd International Conference on Educational Data Mining, July 1-3, 2009, Cordoba, Spain [acceptance rate 33%]

Vasile Rus, Mihai Lintean, Arthur Graesser, Danielle S. McNamara. (2009). Assessing Student Paraphrases Using Lexical Semantics and Word Weighting, Proceedings of the 14^th International Conference on Artificial Intelligence in Education, July 6-10, 2009, Brighton, UK [acceptance rate – 26%]

Mihai Lintean & Vasile Rus. (2009). Paraphrase Identification Using Weighted Dependencies and Word Semantics, Proceedings of the 22^nd International Florida Artificial Intelligence Research Society Conference. Menlo Park, CA: The AAAI Press. [acceptance rate - 38%] 

Archana Bhattarai, Vasile Rus, & Dipankar Dasgupta. (2009). Characterizing Comment Spam in the Blogosphere through Content Analysis, IEEE’s Symposium Series on Computational Intelligence in Cyber Security 2009, March 30 - April 2, 2009, Nashville, TN. [BEST PAPER AWARD] 

Arthur C. Graesser, Zhiqiang Cai, & Vasile Rus. (2008). Question Classification Schemes, Proceedings of the NSF-sponsored Workshop on the Question Generation Shared Task and Evaluation Challenge, Arlington, VA [invited paper]  

Vasile Rus, Zhiqiang Cai, & Arthur C. Graesser. (2008). Question Generation: An Example of a Multi-Year Evaluation Campaign, Proceedings of the NSF-sponsored Workshop on the Question Generation Shared Task and Evaluation Challenge, Arlington, VA [invited paper] 

Vasile Rus, Sameer Mohammed, & Sajjan Shiva. (2008). Automatic Clustering of Defect Reports, Proceedings of the 20^th International Conference on Software and Knowledge Engineering (pp. 291-297), Redwood City, CA [acceptance rate - 40%] 

Vasile Rus, Santhosh Kasturi, & Sajjan Shiva. (2008). Defect Reports Can Be Automatically Clustered Based on Their Summaries, In I. Stamelos and M. Vazirgiannis, Proceedings of the  Artificial Intelligence Techniques in Software Engineering Workshop, 21 July 20 [acceptance rate - 32%] 

Raluca Stoian, Vasile Rus, & Sajjan Shiva. (2008). Predicting Defects in Large Open Source Software,  In V. Rus & T. Lee (Eds.), Proceedings of the 2^nd International Research Workshop on Systems Testing (pp. 79-88), Memphis, TN [invited paper]  

Vasile Rus, Mihai Lintean, Philip M. McCarthy, Danielle S. McNamara, & Arthur C. Graesser. (2008). Paraphrase identification with lexico-syntactic graph subsumption. In D. Wilson & G. Sutcliffe (Eds.), Proceedings of the 21^st International Florida Artificial Intelligence Research Society Conference (pp. 201-206). Menlo Park, CA: The AAAI Press. [acceptance rate - 40%] 

Andrew Neel, Max Garzon, & Vasile Rus. (2008). A Semantic Method for Textual Entailment. In D. Wilson & G. Sutcliffe (Eds.), Proceedings of the 21^st International Florida Artificial Intelligence Research Society Conference (pp. 201-206). Menlo Park, CA: The AAAI Press. [acceptance rate - 40%]  

Philip M. McCarthy, Vasile Rus, Mihai Lintean, Danielle S. McNamara, & Arthur C. Graesser.  (2008). Assessing Forward-, Reverse-, and Average-Entailment Indices on Natural Language Input from the Intelligent Tutoring System, iSTART. In D. Wilson & G. Sutcliffe (Eds.), Proceedings of the 21^st International Florida Artificial Intelligence Research Society Conference (pp. 201-206). Menlo Park, CA: The AAAI Press.[acceptance rate - 40%]  

Vasile Rus, Philip M. McCarthy, Mihai C. Lintean, Arthur C. Graesser, and Danielle S. McNamara, Assessing student self-explanations in an intelligent tutoring system. In  D. S. McNamara and G. Trafton (Eds.), Proceedings of the 29th annual conference of the Cognitive Science Society. Cognitive Science Society. [14% acceptance rate]  

Mihai C. Lintean and Vasile Rus, Large Scale Experiments with Function Tagging. Proceedings of the International Conference on Knowledge Engineering: Principles and Techniques, Cluj-Napoca, Romania, June 5-7, 2007. [27% acceptance rate] 

Vasile Rus and Sajjan Shiva, A General Framework for Information Processing with Application to Quantitative Software Testing, In Proceedings of Workshop on Advances and Innovations in Systems Testing, Memphis, TN, May 6-8, 2007.  [invitation based]

Mihai C. Lintean and Vasile Rus, Naive Bayes and Decision Trees for Function Tagging. In D. Wilson and G. Sutcliffe (Eds.), Proceedings of the twentieth International Florida Artificial Intelligence Research Society Conference (pp. 247-252). Menlo Park, California: The AAAI Press. [42% acceptance rate] 

Philip M. McCarthy, Vasile Rus, Scott A. Crossley, S. C. Bigham, Arthur C. Graesser, and Daniel McNamara, Assessing entailer with a corpus of natural language. In D. Wilson and G. Sutcliffe (Eds.), Proceedings of the twentieth International Florida Artificial Intelligence Research Society Conference (pp. 247-252). Menlo Park, California: The AAAI Press. [42% acceptance rate] 

Vasile Rus, Zhiqiang Cai, and Arthur C. Graesser, Evaluation in Natural Language Generation: The Question Generation Task, Workshop on Shared Tasks and Comparative Evaluation in Natural Language Generation, Arlington, VA, April 20-21, 2007.  [invitation based]

Vasile Rus, Zhiqiang Cai, and Arthur C. Graesser, Experiments on Generating Questions About Facts. Alexander F. Gelbukh (Ed.): Computational Linguistics and Intelligent Text Processing, 8th International Conference, CICLing 2007, Mexico City, Mexico, February 18-24, 2007  [30% acceptance rate]

Vasile Rus, Sireesha Ravi, Mihai C. Lintean, and Philip M. McCarthy, Unsupervised Method for Parsing Coordinated Base Noun Phrases. Alexander F. Gelbukh (Ed.): Computational Linguistics and Intelligent Text Processing, 8th International Conference, CICLing 2007, Mexico City, Mexico, February 18-24, 2007   [30% acceptance rate]

Vasile Rus and Arthur C. Graesser, Deeper Natural Language Processing for Evaluating Student Answers in Intelligent Tutoring Systems, Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06), Pages 1495-1600, July 16-20, 2006, Boston, MA [30% acceptance rate]  

Vasile Rus and Arthur C. Graesser, The Look and Feel of a Confident Entailer, Proceedings of the Language Resources and Evaluation Conference, Pages 1061-1064, May 24-26, 2006, Genoa, Italy [37.5% acceptance rate]  

Vasile, Rus, Dependency-based Textual Entailment, Proceedings of the International Conference of the Florida Artificial Intelligence Research Society, Pages 110-115, May 13-15, 2006, Melbourne, FL [45% acceptance rate]  

Vasile Rus, Two Related Lexico-Syntactic Approaches to Textual Entailment, Proceedings of the Second Recognizing Textual Entailment Challenge, Pages 62-67, April 10, 2006, Venice, Italy [30% acceptance rate]  

Vasile Rus, Philip M. McCarthy and Arthur C. Graesser, Analysis of a Textual Entailer, Proceedings of the 7th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-06), February, 2006, Mexico City, Mexico, Springer-Verlag, Lecture Notes in Computer Science 3878, Pages 287-298, 2006. [33% acceptance rate]  

 Vasile Rus, Art Graesser, Phil McCarthy, King-Ip Lin, “A study on Textual Entailment”, IEEE’s International Conference on Tools with Artificial Intelligence (ICTAI 2005), Pages 326-334, November 14-16, 2005, Hong Kong [12% acceptance rate]   

Vasile Rus, Art Graesser, Kirtan Desai, “Lexico-Syntactic Subsumption for Textual Entailment”, Recent Advances in Natural Language Processing, Pages 444-452, September 21-23, 2005, Borovets, Bulgaria [18% acceptance rate]     

Vasile Rus, Xiangen Hu, Zhiqiang Cai, Art Graesser, Max Louwerse, and Andrew Olney: Augmenting AutoTutor with Deeper Language Processing, the 38^th Annual Meeting of the Society  for Mathematical Psychology, August 4-7, 2005, Memphis, TN  

Christian Hempelmann, Vasile Rus, Art Graesser and Danielle McNamarra, “Evaluating State-of-the-Art Treebank-Style Parsers for Coh-Metrix and Other Learning Technology  Environments”, Proceedings of The Second Workshop on Building Educational Applications using Natural Language Processing, In conjunction with the Annual Meeting of the Association for Computational Linguistics (ACL-2005), Pages 69-76, June 2005, Ann-Harbor, MI [16% acceptance rate]     

Vasile Rus, “A Method to Generate Large Common-Sense Knowledge Bases from Online Lexical Resources”, Florida Artificial Intelligence Research Society International Conference (FLAIRS-05), Pages 635-641, Clearwater, FL [49% acceptance rate]     

Vasile Rus and Kirtan Desai, “Few Inductive Models for Grammatical Relations Recovery”, Clearwater, Florida Artificial Intelligence Research Society International Conference (FLAIRS-05), Pages 851-852, Clearwater, FL [49% acceptance rate]       

Vasile Rus and Christian Hempelmann, “Across-Genres and Empirical Evaluation of State-of-the-Art Treebank-style Parsers”, Language Technologies Conference (LTC-05), Pages 333-3337, April 20-23, 2005, Poznan, Poland [46% acceptance rate]   

Vasile Rus and Kirtan Desai: “Assigning function tags with a simple model”, International Proceedings of the 6^th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2005), Mexico City, Mexico, February 13-19, 2005, Springer-Verlag, Lecture Notes in Computer Science 3406, Pages 112-115, 2005. [27% acceptance rate]     

Vasile Rus and Alex Fit-Florea: “An Algorithm for Discovering the Underlying Logic Structure of Language”, Proceedings of the 8^th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2004), August 9-13, 2004, Auckland, New Zeeland, Springer-Verlag, Lecture Notes in Computer Science 3157, Pages 977-978, 2004. [19% acceptance rate]    

Vasile Rus: “A First Exercise for Evaluating Logic Form Identification Systems”, In Proceedings of the Association of Computational Linguistics Annual Meeting, Companion Volume “Senseval-3: The Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text”, Pages 37-40, Barcelona, Spain, July 2004 [23% acceptance rate]    

Vasile Rus: “Using Decision Trees for Logic Arguments Identification”, International Conference on Artificial Intelligence, Pages 275-280, Las Vegas, Nevada, USA, June 2004   

Vasile Rus: “Experiments with Machine Learning for Logic Arguments Identification”, Midwest Artificial Intelligence Conference (MAICS-2004), Pages 40-47, April 2004, Schaumburg, IL [52% acceptance rate]   

Vasile Rus: “From English Sentences to First Order Logic Statements”, Hawaii International Conference on Computer Sciences (HICCOMPUTERS 2004), 6 pages, January 2004, Honolulu, HI, accepted    

Vasile Rus: “A Highly Accurate Iterative Algorithm for Logic Form Identification”, International Association of Science and Technology for Economic Development (IASTED) Conference in Information and Knowledge Sharing (IASTED-IKS), Pages 126-131, November 2003, Scottsdale, AZ [47% acceptance rate]   

Vasile Rus: “A Bottom-Up Algorithm for Logic Form Transformation of Texts”, The 2003 International Conference on Artificial Intelligence (IC-AI'03), 6 pages, June 23 - 26, 2003, Monte Carlo Resort, Las Vegas, Nevada, USA     

Vasile Rus, Dan I. Moldovan and Orest Bolohan: Bracketing Compound Nouns for Logic Form Derivation, Proceedings of the Florida Artificial Intelligence Research Society International Conference (FLAIRS 2002) Conference, Pages 198-202, May 2002, Pensacola, Florida [54% acceptance rate]    

Vasile Rus: High Precision Logic Form Transformation, Proceedings of the 13^th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Pages 288-295, November 2001, Dallas, TX [33% acceptance rate]     

Dan I. Moldovan and Vasile Rus: Logic Form Transformation of WordNet and its Applicability to Question Answering, Annual Meeting of Association of Computational Linguistics (ACL) 2001, Pages 394-401, Toulouse, France [16% acceptance rate]   

Sanda Harabagiu, Dan Moldovan, Marius Pasca, Mihai Surdeanu, Rada Mihalcea, Roxana Girju, Vasile Rus, Finley Lacatusu, Paul Moraescu, Razvan Bunescu - Answering Complex, List and Context Questions with LCC's Question-Answering Server. In Proceedings of National Institute for Standards and Technology (NIST)’s 10^th TExt Retrieval Conference (TREC 10), Pages 355-361, Gaithersburg, Maryland, November 2001   

Sanda Harabagiu, Dan Moldovan, Paul Morarescu, Finley Lacatusu, Rada Mihalcea, Vasile Rus, Roxana Girju. GISTexter: A System for Summarizing Text Documents, Workshop on Text Summarization, In conjunction with International Conference of the Association for Computing Machinery's (ACM) Special Interest Group on Information Retrieval (SIGIR 2001), New Orleans, 2001   

Dan I. Moldovan and Vasile Rus: Transformation of WordNet Glosses into Logic Forms, Florida Artificial Intelligence Research Society International Conference (FLAIRS 2001), Pages 459-463, Key West, Florida, May 2001  

Sanda Harabagiu, Dan Moldovan, Marius Pasca, Rada Mihalcea, Mihai Surdeanu, Razvan Bunescu, Roxana Girju, Vasile Rus and Paul Morarescu: The role of Lexico-Semantic Feedbacks in Open-Domain Textual Question Answering, Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics (ACL-2001), Pages 274-281, July 2001, Toulouse, France [16% acceptance rate]   

Sanda Harabagiu, Dan Moldovan, Marius Pasca, Rada Mihalcea, Mihai Surdeanu, Razvan Bunescu, Roxana Girju, Vasile Rus and Paul Morarescu: FALCON - Boosting Knowledge for Answer Engines. Proceedings of National Standards and Technologies' (NIST) 9th Text Retrieval Conference (TREC-9), Pages 479-487, November 2000, Gaithersburg, Maryland  

Dan Moldovan, Sanda Harabagiu, Marius Pasca, Rada Mihalcea, Roxana Girju, Richard Goodrum and Vasile Rus The Structure and Performance of an Open-Domain Question Answering System, in Proceedings of Annual Meeting of Association of Computational Linguistics (ACL 2000), Pages 563-570, Hong Kong, October, 2000 [19% acceptance rate]   

Dan Moldovan, Roxana Girju and Vasile Rus - Domain-Specific Knowledge Acquisition from Text . In Proceedings of the Applied Natural Language Processing (ANLP-2000) Conference, Pages 268-275, Seattle, WA, April-May 2000   

Dan Moldovan, Sanda Harabagiu, Marius Pasca, Rada Mihalcea, Richard Goodrum, Roxana Girju and Vasile Rus, LASSO: A Tool for Surfing the Answer Net, in Proceedings of the National Standards and Technologies' (NIST) Text Retrieval Conference (TREC-8), Pages 171-184, November, 1999        

Non-Refereed Publications

Azevedo, R., Witherspoon, A., Graesser, A. McNamara, D., Chauncey, A., Siler, E., Cai, Z., Rus, V., & Lintean, M. (2009). MetaTutor: Analyzing self-regulated learning in a tutoring systemfor biology. In V. Dimitrova, R. Mizoguchi, B. du Boulay, & A. Graesser (Eds.) Building learning systems that care: From knowledge representation to affective modeling (pp. 635-637). Amsterdam, The Netherlands: IOS Press. [acceptance rate - 27%]

Presentations - Conference (refereed *)

Towards Non-Intrusive Assessment in Dialogue-based Intelligent Tutoring Systems, The 2nd International Conference on Smart Learning Environments, September 24, Sinaia, Romania

Hierarchical Dialogue Act Classification in Online Tutoring Sessions, The Eighth International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, June 27, 2015.

DeepTutor: Integrating Learning Progressions In Unsupervised After-school Online Intelligent Tutoring, The 17th International Conference on Artificial Intelligence in Education (AIED 2015), June 24, 2015, Madrid, Spain.

Unsupervised Discovery of Tutorial Dialogue Modes in Human-to-Human Tutorial Data, The 3^rd Generalized Intelligent Tutoring Framework Symposium, June 17-18, Orlando, FL.

Mining Gap-fill Questions from Tutorial Dialogues, The 7th International Conference on Educational Data Mining, July 4, 2014, London, UK

Assessing Students' Prior Knowledge From Tutorial Dialogues, The 7th International Conference on Educational Data Mining, July 4, 2014, London, UK

Macro-adaptation in Conversational Intelligent Tutoring Matters, The 12th International Conference on Intelligent Tutoring Systems, June 8, Honolulu, Hawaii

A Bilingual Analysis of Cohesion in a Corpus of Leader Speeches, The 27th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2014), May 23, Pensacola Beach, FL, USA

Opportunities and Challenges in Semantic Similarity, The 27th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2014), Invited Plenary Talk, May 22, Pensacola Beach, FL, USA.

DeepTutor: Towards Macro- and Micro-Adaptive Conversational Intelligent Tutoring at Scale, ACM’s Learning@Scale Conference, Atlanta, GA, March 4, 2014

DeepTutor – Promoting Deep Learning of Complex Science Topics, Annual Principal Investigator Meeting, Institute for Education Sciences, Washington, DC, September 26, 2013

Recommendations for the Generalized Intelligent Framework for Tutoring based on the Development of the DeepTutor Tutoring Service, Workshop on Generalized Intelligent Framework for Tutoring (GIFT), The 16th International Conference on Artificial Intelligence in Education (AIED 2013), July 9-13, Memphis, TN.

The Role of Learning Progressions In The Development Of An Intelligent Tutoring Systems For All Ages, Improving Middle School Science Instruction Using Cognitive Science - A National Conference on May 21-22, 2013 in Washington, DC (poster presentation)

Experiments with Semantic Similarity Measures based on LDA and LSA, The 1st International Conference on Statistical Speech and Language Processing (SLSP 2013), July 29-31, Tarragona, Spain.

Concepts versus Latent Topics. In Proceedings of The 23rd Meeting of The Society for Text and Discourse, July 16-18, Valencia, Spain

Keynote Speaker: Language Technologies for Research and Development, September 25-26, 2012, Romanian Academy, Bucharest, Romania

Plenary Talk: Learning Progressions-driven Intelligent Tutoring Systems - Annual Principal Investigator Meeting, Institute for Education Sciences, Washington, DC, September 5, 2012

Invited Talk: Language Processing From Sailors to Tutors to Software Developers, The University of Sydney, Department of Electrical Engineering, April 4, 2012

Invited Talk: Promoting Deep Learning of Science with DeepTutor, Army Research Lab Workshop on Generalized Intelligent Framework for Tutoring, May 16-17, 2012

Plenary Talk, AAAI Fall Symposium on Question Generation, November 5, 2011, Arlington, VA 

Natural Language based Knowledge Representation, Cognitive Science Seminar, Institute for Intelligent Systems, Memphis, TN, November 8, 2011

DeepTutor – An Intelligent Tutoring System that Promotes Deep Science Learning, Annual Principal Investigator Meeting, Institute for Education Sciences, Washington, DC, September 7, 2011

Dissimilarity Kernels for Paraphrase Identification, The 24th International Florida Artificial Intelligence Research Society Conference, Palm Beach, FL, May 19, 2011.

A Linguistic Analysis of Student Generated Paraphrases, Proceedings of the 24^th International Florida Artificial Intelligence Research Society Conference, Palm Beach, FL, May 19, 2011.

Automated Speech Act Classification for Online Chat, The 22^nd Midwest Artificial Intelligence and Cognitive Science Conference, Cincinatti, OH, April 2, 2011.

The Ubiquity of Natural Language in a Linked, Knowledge-Based World, Plenary Talk, The 21^st Midwest Artificial Intelligence and Cognitive Science Conference, South Bend, IN, April 18, 2010

Automatic Speech Act Classification in Arabic, Workshop on Natural Language Processing in Social Sciences, Buenos Aires, Argentina, May 2010

An Overview of The First Question Generation Shared Task and Evaluation Challenge, The Third Workshop on Question Generation, Pittsburgh, PA, June 2010

The Ubiquity of Natural Language in a Linked, Knowledge-driven World, Computer Science Colloquium, Memphis, TN, November 19, 2010

The First Question Generation Shared Task and Evaluation Challenge, Intelligent Tutoring Systems course, Department of Psychology, The University of Memphis, November 18, 2010

Assessing Student Paraphrases Using Lexical Semantics and Word Weighting, The 14^th International Conference on Artificial Intelligence in Education, Brighton, UK, July 9, 2009

Building Resources for an Open Task on Question Generation, The 2^nd Workshop on Question Generation, Brighton, UK, July 6, 2009

Where Next in Knowledge Representation?, Plenary Talk, The 2^nd Knowledge Engineering: Principles and Techniques International Conference, Cluj, Romania, July 3, 2009

MLeXAI: Biomedical Term Classification, Workshop on MLeXAI: Machine Learning Experiences in AI: A Multi-Institutional Project, In conjunction with the 22 FLAIRS Conference, Sanibel Island, FL, May 18, 2009

Challenges, Solutions, and Surprises in Sentence-level Paraphrase Identification, Brown Bag Series, Institute for Intelligent Systems, Memphis, TN, April 13, 2009

Data-driven Defect Management and Testing Processes in Large-scale Software Development, International Research Workshop on Advances and Innovations in Software Testing, Memphis, TN, May 4, 2009

MLxAI: Biomedical Term Classification, The Seventh Annual Conference of the Consortium for Computing Sciences in Colleges – Mid-South, Conference, April 4, 2009

Defect Reports Can Be Automatically Clustered Based on Their Summaries, Artificial Intelligence Techniques in Software Engineering Workshop, Patras, Greece, July 21, 2008 

On Sentence-to-Sentence Relations, Society for Text and Discourse, Memphis, TN, July 13, 2008 

Automatic Clustering of Defect Reports, International Conference on Software and Knowledge Engineering, Redwood City, CA, July, 5, 2008 

Paraphrase identification with lexico-syntactic graph subsumption, International Conference of the Florida Artificial Intelligence Research Society, May 16, 2008 

Predicting Defects in Large Open Source Software, Workshop on Advances and Innovations in Software Testing, Memphis, TN, May 5, 2008 

Text To Text Generation, Workshop on Shared Tasks in Natural Language Generation, Arlington, VA, April 21, 2007 

Evaluation in Natural Language Generation: The Question Generation Task, Workshop on Shared Tasks in Natural Language Generation, Arlington, VA, April 20, 2007  

Large Scale Experiments with Functional Tagging, Knowledge Engineering: Principles and Techniques, Cluj-Napoca, Romania, June 7, 2007 

Natural Language based Knowledge Representations, Computer Science Colloquium Series, Department of Computer Science, University of Memphis, Spring 2007, Memphis, TN, March 2, 2007 

Experiments with Generating Questions About Facts, International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), Mexico City, Mexico, February 22, 2007 

Unsupervised Method for Base Noun Phrase Parsing, International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), Mexico City, Mexico, February 22, 2007 

Deeper Natural Language Processing for Evaluating Student Answers in Intelligent Tutoring Systems, National Conference of the American Association for Artificial Intelligence (AAAI), Boston, MA, July 15, 2006

The Look and Feel of a Textual Entailer, Language Resources and Evaluation Conference (LREC), Genoa, Italy, May 24, 2006

A Dependency Approach To Textual Entailment, International Conference of the Florida Artificial Intelligence Research Society (FLAIRS), Melbourne, FL, 13 May, 2006

Two Related Lexico-Syntactic Approaches to Entailment, Second Recognizing Textual Entailment Challenge (RTE-2), Venice, Italy, April 11, 2006

Towards a Base Noun Phrase Parser with Web Counts, Mid-South Computing Sciences in Colleges Consortium Conference, Memphis, TN, April 1, 2006

Analysis of a Textual Entailer, International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), Mexico City, Mexico, February 21, 2006

A Study of a Textual Entailer, IEEE’s International Conference of Artificial Intelligence, Hong Kong, November 16, 2005 

 Lexico-Syntactic Subsumption for Textual Entailment, Recent Advances in Natural Language Processing Borovetz, Bulgaria, September 18, 2005

Augmenting AutoTutor with Deeper Natural Language Processing, Mathematical Psychology Conference, August 2005, Memphis, TN 

Building Large Knowledge-Bases from Online Dictionaries, FLAIRS 2005, May 2005, Clearwater, FL 

Across-Genres and Empirical Evaluation of Treebank-Style Parsers, Language and Technology Conference, April 2005, Poznan, Poland 

Mining Answers from Large Collections, Computational Applications and Cyber-infrastructure Symposium, Murfreesboro, TN, January 2004 

Using Decision Trees for Logic Arguments Identification, International Conference on Artificial Intelligence, Las Vegas, NV, June 2004 

Learning Functional Arguments, Midwest Artificial Intelligence and Cognitive Science Conference (MAICS 2004), Roosevelt University, Chicago, IL, March 2004

Bracketing Compound Nouns for Logic Form Derivation, FLAIRS, May 2002 

High Precision Logic Form Transformation, ICTAI, November 2001 

Transformation of WordNet Glosses into Logic Form, FLAIRS, May 2001 

Presentations - Universities/Industry (refereed *)

Semantic Similarity Using Quadratic Assignment, Computer Science Colloquium, October 26, 2012

Data-driven Defect Management and Testing Processes in Large-scale Software Development, International Research Workshop on Advances and Innovations in Software Testing, Memphis, TN, May 4, 2009 

Trends in Language and Information Processing, Department of Computer Science, University of Mississippi, September 10, 2008 

Advanced Defect Analysis Methods, Workshop on Software Testing sponsored by International Paper, Memphis, TN, January 11, 2008 

Knowledge Management in Modern Software Testing, Workshop on Knowledge Management in Software Testing sponsored by Nomura Research Japan, Memphis, TN, November 7, 2007 

Mining Text from Large and Structurally-Diverse Repositories, MIS Department, Fogelman College of Business and Economics, The University of Memphis, Memphis, TN, October 26, 2007 

An Overview of BioNLP, Bioinformatics Colloquium, The University of Memphis, Memphis, TN, September 28, 2007 

A General Framework for Information Processing with Application to Quantitative Software Testing, Workshop on Advances and Innovations in Software Testing, Memphis, TN, May 5, 2007 

Adaptive Question Answering in AutoTutor, AutoTutor Research Group Meeting, Memphis, TN, February 19, 2007

Natural Language based Knowledge Representations, Cognitive Brown Bag Series, Fall 2006, Memphis, TN, November 13, 2006

Adaptive Question Answering, Coh-Metrix Research Group Meeting, Memphis, TN, November 6, 2006 

Deeper Natural Language Processing for AutoTutor, AutoTutor Research Meeting, Institute for Intelligent Systems, Memphis, TN, July 24, 2006 

 A Survey of Computational Linguistics Tools and Applications, Learning Technologies Seminar, Institute For Intelligent Systems, The University of Memphis, January 25, 2006

Logic and Language, Knowledge Representation Class taught by Dr. Lee McCauley November 8, 2005

Lexico-Syntactic Graphs for Deeper Text Understanding, CS Colloquium, Memphis, TN September 16, 2005

Lexico-Syntactic Subsumption for Textual Entailment, Learning Technologies Meeting, Institute for Intelligent Systems, September 07, 2005

The Impact of World Knowledge on Open Domain Question Answering, Department of Computer Science, University of North Texas, Denton, TX, November 2004

Using World Knowledge for Question Answering, University of Memphis/Fedex Institute of Technology, March 2004, Memphis, TN 

Logic and Language, Florida Atlantic University, April 2003 

Logic Form and Its Application to Question Answering, Toyota Technological Institute, April 2003 

Logic Form and Its Applications, Purdue University,  March 2003 

Concept-based Representation: Combining syntax and semantics, Technical University of Cluj-Napoca, January 2002 

Natural Language Processing/Computational Linguistics, Cognitive Science Seminar coordinated by Dr. Max Louwerse, November 9, 2005

Other Presentations (refereed *)

Towards Non-Intrusive Assessment in Dialogue-based Intelligent Tutoring Systems, The 2nd International Conference on Smart Learning Environments, September 24, Sinaia, Romania

Hierarchical Dialogue Act Classification in Online Tutoring Sessions, The Eighth International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, June 27, 2015.

DeepTutor: Integrating Learning Progressions In Unsupervised After-school Online Intelligent Tutoring, The 17th International Conference on Artificial Intelligence in Education (AIED 2015), June 24, 2015, Madrid, Spain.

Unsupervised Discovery of Tutorial Dialogue Modes in Human-to-Human Tutorial Data, The 3^rd Generalized Intelligent Tutoring Framework Symposium, June 17-18, Orlando, FL.

Prospects of Textual Entailment in Intelligent Tutoring Systems, Learning Technologies Seminar, Institute for Intelligent Systems, University of Memphis, December 2004

Appendix A

Appendix B

Appendix C

Appendix D

Appendix E