Papers

* denotes equal contribution, α-β denotes alphabetical author ordering

“Can Language Models Learn to Listen?”
Evonne Ng*, Sanjay Subramanian*, Dan Klein, Angjoo Kanazawa, Trevor Darrell, Shiry Ginosar.
ICCV 2023.
[paper] [code] [project page]

“Modular Visual Question Answering via Code Generation.”
Sanjay Subramanian, Medhini Narasimhan, Kushal Khangaonkar, Kevin Yang, Arsha Nagrani, Cordelia Schmid, Andy Zeng, Trevor Darrell, Dan Klein.
ACL 2023.
[paper] [code] [Google AI blog]

“ReCLIP: A Strong Zero-shot Baseline for Referring Expression Comprehension.”
Sanjay Subramanian, Will Merrill, Trevor Darrell, Matt Gardner, Sameer Singh, and Anna Rohrbach.
ACL 2022.
[paper] [code]

“Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering.”
Ben Bogin, Sanjay Subramanian, Matt Gardner, and Jonathan Berant.
TACL 2021.
[paper] [code]

“MedICaT: A Dataset of Medical Images, Captions, and Textual References.”
Sanjay Subramanian, Lucy Wang, Sachin Mehta, Ben Bogin, Madeleine van Zuylen, Sravanthi Parasa, Sameer Singh, Matt Gardner, and Hannaneh Hajishirzi.
Findings of EMNLP 2020.
[paper] [data and code] [talk for Scholarly Document Processing (SDP) workshop]

“Evaluating Models’ Local Decision Boundaries via Contrast Sets.”
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou.
Findings of EMNLP 2020.
[paper] [data]

“Obtaining Faithful Interpretations from Compositional Neural Networks.”
Sanjay Subramanian*, Ben Bogin*, Nitish Gupta*, Tomer Wolfson, Sameer Singh, Jonathan Berant, and Matt Gardner.
ACL 2020.
[paper] [code] [conference talk]

“Analyzing Compositionality of Visual Question Answering.”
Sanjay Subramanian, Sameer Singh, and Matt Gardner.
ViGIL Workshop @ NeurIPS 2019.
Spotlight Paper
[paper]

“AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models.”
Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, and Sameer Singh.
EMNLP 2019 (Demo Papers).
Best Demo Paper
[paper] [webpage]

“Correlation Clustering with Same-Cluster Queries Bounded by Optimal Cost.”
Barna Saha (α-β) and Sanjay Subramanian (α-β).
European Symposium on Algorithms (ESA) 2019.
[paper] [code]

“Improving Generalization in Coreference Resolution via Adversarial Training.”
Sanjay Subramanian and Dan Roth.
*SEM 2019.
[paper] [code]

“Evaluation of Named Entity Coreference.”
Oshin Agarwal*, Sanjay Subramanian*, Ani Nenkova, and Dan Roth.
Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC) at NAACL 2019.
[paper]