| BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation J Dhamala, T Sun, V Kumar, S Krishna, Y Pruksachatkun, KW Chang, ... ACM FAccT Conference 2021, 2021 | 196 | 2021 |
| The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective S Krishna, T Han, A Gu, J Pombra, S Jabbari, S Wu, H Lakkaraju Interpretable Machine Learning in Healthcare in ICML 2022, 2022 | 150* | 2022 |
| OpenXAI: Towards a Transparent Evaluation of Model Explanations C Agarwal, S Krishna, E Saxena, M Pawelczyk, N Johnson, I Puri, M Zitnik, ... Advances in neural information processing systems, 2023 | 93 | 2023 |
| Explaining machine learning models with interactive natural language conversations using TalkToModel D Slack, S Krishna, H Lakkaraju, S Singh Nature Machine Intelligence, 1-11, 2023 | 42* | 2023 |
| Adept: Auto-encoder based differentially private text transformation S Krishna, R Gupta, C Dupuy Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 32 | 2021 |
| Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal U Gupta, J Dhamala, V Kumar, A Verma, Y Pruksachatkun, S Krishna, ... Findings of the Association for Computational Linguistics: ACL 2022, 2022 | 30 | 2022 |
| Rethinking Stability for Attribution-based Explanations C Agarwal, N Johnson, M Pawelczyk, S Krishna, E Saxena, M Zitnik, ... ICLR 2022 Workshop on PAIR^2Struct: Privacy, Accountability …, 2022 | 29 | 2022 |
| Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification Y Pruksachatkun, S Krishna, J Dhamala, R Gupta, KW Chang Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 | 29 | 2021 |
| Post Hoc Explanations of Language Models Can Improve Language Models S Krishna, J Ma, D Slack, A Ghandeharioun, S Singh, H Lakkaraju Advances in Neural Information Processing Systems, 2023 36, 2023 | 18* | 2023 |
| Are Large Language Models Post Hoc Explainers? N Kroeger, D Ley, S Krishna, C Agarwal, H Lakkaraju arXiv preprint arXiv:2310.05797, 2023 | 7 | 2023 |
| Measuring Fairness of Text Classifiers via Prediction Sensitivity S Krishna, R Gupta, A Verma, J Dhamala, Y Pruksachatkun, KW Chang Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 7 | 2022 |
| Black-Box Access is Insufficient for Rigorous AI Audits S Casper, C Ezell, C Siegmann, N Kolt, TL Curtis, B Bucknall, A Haupt, ... arXiv preprint arXiv:2401.14446, 2024 | 6 | 2024 |
| Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten S Krishna, J Ma, H Lakkaraju The Fortieth International Conference on Machine Learning (ICML), 2023, 2023 | 6 | 2023 |
| Towards Realistic Single-Task Continuous Learning Research for NER J Payan, Y Merhav, H Xie, S Krishna, A Ramakrishna, M Sridhar, R Gupta Findings of the Association for Computational Linguistics: EMNLP 2021, 2021 | 5 | 2021 |
| Finetext: text classification via attention-based language model fine-tuning Y Tao, S Gupta, S Krishna, X Zhou, O Majumder, V Khare Amazon Machine Learning Conference (AMLC) 2020, 2019 | 3 | 2019 |
| On the Intersection of Self-Correction and Trust in Language Models S Krishna arXiv preprint arXiv:2311.02801, 2023 | 2 | 2023 |
| On the Trade-offs between Adversarial Robustness and Actionable Explanations S Krishna, C Agarwal, H Lakkaraju arXiv preprint arXiv:2309.16452, 2023 | 2* | 2023 |
| Towards classification parity across cohorts A Patel, R Gupta, M Harakere, S Krishna, A Alok, P Liu ML-IRL Workshop at ICLR 2020, 2020 | 2 | 2020 |
| Proceedings of the First Workshop on Trustworthy Natural Language Processing Y Pruksachatkun, A Ramakrishna, KW Chang, S Krishna, J Dhamala, ... Proceedings of the First Workshop on Trustworthy Natural Language Processing, 2021 | 1 | 2021 |
| Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence B Peng, D Goldstein, Q Anthony, A Albalak, E Alcaide, S Biderman, ... arXiv preprint arXiv:2404.05892, 2024 | | 2024 |
Himabindu LakkarajuAssistant Professor, Harvard UniversityVerified email at seas.harvard.edu
