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Gontier, N., Sinha, K., Reddy, S., & Pal, C. J. (2020, December). Measuring systematic generalization in neural proof generation with transformers [Paper]. 34th Conference on Neural Information Processing Systems (NeurIPS 2020) (17 pages). External link
Krojer, B., Poole-Dayan, E., Voleti, V., Pal, C. J., & Reddy, S. (2023, December). Are Diffusion Models Vision-And-Language Reasoners? [Paper]. 37th Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA (21 pages). External link
Madsen, A., Anbil Parthipan, S. C., & Reddy, S. (2024, August). Are self-explanations from Large Language Models faithful? [Paper]. 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Hybrid, Bangkok, Thailand. External link
Madsen, A., Reddy, S., & Anbil Parthipan, S. C. (2024, July). Faithfulness Measurable Masked Language Models [Paper]. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria. External link
Madsen, A., Reddy, S., & Anbil Parthipan, S. C. (2023). Post-hoc Interpretability for Neural NLP: A Survey. ACM Computing Surveys, 55(8), 1-42. External link
Madsen, A., Meade, N., Adlakha, V., & Reddy, S. (2022, December). Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining [Paper]. Findings of the Association for Computational Linguistics (EMNLP 2022), Abu Dhabi, United Arab Emirates. External link
