(Book Chapter) Ovchinnikova E., Montazeri N., Alexandrov T., Hobbs J.R., McCord M.C., Mulkar-Mehta R. (2014) Abductive Reasoning with a Large Knowledge Base for Discourse Processing. In: Bunt H., Bos J., Pulman S. (eds) Computing Meaning. Text, Speech and Language Technology, vol 47. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7284-7_7

(Book Chapter) Hobbs, J. R., & Mulkar-Mehta, R. (2013). Toward a Formal Theory of Information Structure. In Evolution of Semantic Systems (pp. 101-126). Springer, Berlin, Heidelberg.

(Book) Mulkar-Mehta, R., Granular Causality: Discovering Causality in Natural Language, LAP LAMBERT Academic Publishing (2012), (ISBN 10:3847324470, ISBN 13:978-3847324478) Available from Amazon.com

(Conference Paper) Silgard, E., Tharp, M., & Mulkar-Mehta, R. (2012). Temporal Relation Extraction from Medical Discharge Summaries. 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology, 132-132, (HISB 2012), UCSD, La Jolla, CA

Mulkar-Mehta, R., Welty, C., Hobbs, J. R., Hovy, E. H., Using Part-of Relations to Discover Causality, Machine Reading Phase 3 Kickoff meeting, 2011, Seattle, WA

Mulkar-Mehta, R., Welty, C., Hobbs, J. R., Hovy, E. H., Granularity in Natural Language Discourse, Reasoning with Text, 2011 Workshop, at ICT, Los Angeles, CA

(Ph.D. Thesis) Mulkar-Mehta, R. (2011). Granular causality for learning by reading. University of Southern California.

(Journal Paper) Pan, F., Mulkar-Mehta, R., & Hobbs, J. (2011). Annotating and Learning Event Durations in Text. Computational Linguistics, 37, 727-752.

(Conference Paper) Ovchinnikova, E., Montazeri, N., Alexandrov, T., Hobbs, J., McCord, M., & Mulkar-Mehta, R. (2011). Abductive Reasoning with a Large Knowledge Base for Discourse Processing. In Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011)

(Conference Paper) Mulkar-Mehta, R., Gordon, A., Hobbs, J. R., & Hovy, E. Causal markers across domains and genres of discourse. In Proceedings of the sixth international conference on Knowledge capture, pp. 183-184. 2011. [poster]

(Conference Paper) Mulkar-Mehta, R., Hobbs, J. R., & Hovy, E. (2011). Granularity in natural language discourse. In Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011).

(Conference Paper) Mulkar-Mehta, R., Hobbs, J. R., & Hovy, E. H. (2011, March). Applications of Discovery of Granularity Structures in Natural Language Discourse. In AAAI Spring Symposium: logical formalizations of commonsense reasoning.

(Conference Paper) Mulkar-Mehta, R., Welty, C., Hobbs, J., & Hovy, E. (2011, March). Using Part-Of Relations for Discovering Causality. In Twenty-Fourth International FLAIRS Conference. (Nominated for Best Student Paper Award [PPT]

Mulkar-Mehta, R., Jerry Hobbs, Causal Granularity: Answering "How" Events Happen, At the Abductive Inference ARO MURI 2010 Workshop

Mulkar-Mehta, R., Hobbs, J., Liu, C., & Zhou, X. (2009). Discovering Causal and Temporal Relations in Biomedical Texts. AAAI Spring Symposium: Learning by Reading and Learning to Read.

Hobbs, J. R., & Mulkar-Mehta, R.(2008). Using Abduction for Video-Text Coreference. In Proceedings of BOEMIE 2008 Workshop on Ontology Evolution and Multimedia Information Extraction.

Barker, K., Agashe, B., Chaw, S., Fan, J., Friedland, N., Glass, M.R., Hobbs, J., Hovy, E., Israel, D., Kim, D.S., Mulkar-Mehta, R., Patwardhan, S., Porter, B., Tecuci, D., & Yeh, P.Z. (2007). Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned. AAAI.

Mulkar-Mehta, R., Hobbs, J., & Hovy, E. (2007). Learning from Reading Syntactically Complex Biology Texts. AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning.

Pan, F., Mulkar-Mehta, R., & Hobbs, J. (2007). Modeling and Learning Vague Event Durations for Temporal Reasoning. In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI), Nectar Track, pp. 1659-1662, Vancouver, Canada.

Mulkar, R., Hobbs, J., Hovy, E., Chalupsky, H., & Lin. C.Y. Learning by reading: Two experiments. In Proceedings of IJCAI 2007 workshop on Knowledge and Reasoning for Answering Questions, pp. 287-296. 2007.

Pan, F., Mulkar-Mehta, R., & Hobbs, J. R. (2006, July). Learning event durations from event descriptions. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (pp. 393-400). (Acceptance rate: 23%)

Pan, F., Mulkar, R., & Hobbs, J. R. (2006, May). An Annotated Corpus of Typical Durations of Events. In LREC (pp. 77-82).

Pan, F. Mulkar, R., Hobbs, J. R. Extending TimeML with Typical Durations of Events, In Proceedings of Annotating and Reasoning about Time and Events workshop at the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics (COLING-ACL), 2006