COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images. - Ben Bogin; Shivanshu Gupta; Matt Gardner 001; Jonathan Berant (EMNLP (1), 2021)

Unobserved Local Structures Make Compositional Generalization Hard. - Ben Bogin; Shivanshu Gupta; Jonathan Berant (EMNLP, 2022)

Successive Prompting for Decomposing Complex Questions. - Dheeru Dua; Shivanshu Gupta; Sameer Singh 001; Matt Gardner 001 (EMNLP, 2022)

Structurally Diverse Sampling for Sample-Efficient Training and Comprehensive Evaluation. - Shivanshu Gupta; Sameer Singh 001; Matt Gardner 001 (EMNLP (Findings), 2022)

Structurally Diverse Sampling Reduces Spurious Correlations in Semantic Parsing Datasets. - Shivanshu Gupta; Sameer Singh 001; Matt Gardner 001 (CoRR, 2022)

Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages. - Shivanshu Gupta; Yoshitomo Matsubara; Ankit Chadha; Alessandro Moschitti (ACL (Findings), 2023)

Coverage-based Example Selection for In-Context Learning. - Shivanshu Gupta; Matt Gardner 001; Sameer Singh 001 (EMNLP (Findings), 2023)

GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks. - Shivanshu Gupta; Clemens Rosenbaum; Ethan R. Elenberg (ICML, 2024)

Leveraging Code to Improve In-Context Learning for Semantic Parsing. - Ben Bogin; Shivanshu Gupta; Peter Clark; Ashish Sabharwal (NAACL-HLT, 2024)

Unraveling Indirect In-Context Learning Using Influence Functions. - Hadi Askari; Shivanshu Gupta; Terry Tong; Fei Wang 060; Anshuman Chhabra; Muhao Chen 001 (CoRR, 2025)

LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions. - Hadi Askari; Shivanshu Gupta; Fei Wang 060; Anshuman Chhabra; Muhao Chen 001 (CoRR, 2025)

Leveraging In-Context Learning for Language Model Agents. - Shivanshu Gupta; Sameer Singh 001; Ashish Sabharwal; Tushar Khot; Ben Bogin (CoRR, 2025)