| 2024 | ICML | GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks. | Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg |
| 2024 | NAACL | Leveraging Code to Improve In-Context Learning for Semantic Parsing. | Ben Bogin, Shivanshu Gupta, Peter Clark, Ashish Sabharwal |
| 2023 | ACL | Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages. | Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha, Alessandro Moschitti |
| 2023 | EMNLP | Coverage-based Example Selection for In-Context Learning. | Shivanshu Gupta, Matt Gardner, Sameer Singh |
| 2022 | EMNLP | Unobserved Local Structures Make Compositional Generalization Hard. | Ben Bogin, Shivanshu Gupta, Jonathan Berant |
| 2022 | EMNLP | Successive Prompting for Decomposing Complex Questions. | Dheeru Dua, Shivanshu Gupta, Sameer Singh, Matt Gardner |
| 2022 | EMNLP | Structurally Diverse Sampling for Sample-Efficient Training and Comprehensive Evaluation. | Shivanshu Gupta, Sameer Singh, Matt Gardner |
| 2021 | EMNLP | COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images. | Ben Bogin, Shivanshu Gupta, Matt Gardner, Jonathan Berant |