Can we use computational modeling to inform our understanding of semantics, pragmatics and social science ? I think the answer is yes
I am currently studying intergroup biases in communication with Assistant Professor Jessy Li and Professor David Beaver. I was inspired by a seminar in my first semester with David, where he talked about the Linguistic Intergroup Bias. To summarize my research questions succinctly — what are the linguistic properties that characterize and distinguish in-group speech from out-group speech, and how can we infer these properties using machine learning?
I completed my Masters at the University of Rochester, where I worked in the Formal and Computational Semantics Lab with Assistant Professor Aaron Steven White. My research focused on the wide breadth of generalizations available across predicates and arguments in English.
Venkata S Govindarajan, David I. Beaver, Kyle Mahowald, Jessy Li. 2023. Counterfactual Probing for the Influence of Affect and Specificity on Intergroup Bias. In Findings of the Association for Computational Linguistics (ACL). Toronto, Canada: Association for Computational Linguistics. July 2023. [pdf] [bib] [data+code] [poster]
Venkata S Govindarajan, Katherine Atwell, Barea Sinno, Malihe Alikhani, David I. Beaver, Jessy Li. 2023. How people talk about each other: Modeling Generalized Intergroup Bias and Emotion. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL). Dubrovnik, Croatia: Association for Computational Linguistics. May 2023. [pdf] [bib] [data] [slides] [poster]
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan, et al. 2022. longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks. In Proceedings of the First Workshop on Dynamic Adversarial Data Collection. Seattle, WA: Association for Computational Linguistics. July 2022. [pdf] [bib]
Venkata S Govindarajan, Benjamin T. Chen, Rebecca Warholic, Katrin Erk & Junyi Jessy Li. 2020. Help! Need Advice on Identifying Advice. In Proceedings of The 2020 Conference on Empirical Methods in Natural Language Processing. Online: Association for Computational Linguistics. November 2020. [pdf] [bib] [data] [slides]
Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha, Venkata Govindarajan, Dee Ann Reisinger, Tim Vieira, Keisuke Sakaguchi, Sheng Zhang, Francis Ferraro, Rachel Rudinger, Kyle Rawlins, & Benjamin Van Durme. 2020. The Universal Decompositional Semantics Dataset and Decomp Toolkit. In Proceedings of The 12th Language Resources and Evaluation Conference, 5698-5707. Marseille, France: European Language Resources Association. May 2020. [pdf] [bib] [data]
Venkata Govindarajan, Benjamin Van Durme, & Aaron Steven White. 2019. Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements. In Transactions of the Association for Computational Linguistics 7. 501–517. [pdf] [bib] [data] [slides]