Satyapriya Krishna
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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
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
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
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
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
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
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
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
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
Black-Box Access is Insufficient for Rigorous AI Audits
S Casper, C Ezell, C Siegmann, N Kolt, TL Curtis, B Bucknall, A Haupt, ...
ACM FAccT Conference 2024, 2024
Are Large Language Models Post Hoc Explainers?
N Kroeger, D Ley, S Krishna, C Agarwal, H Lakkaraju
arXiv preprint arXiv:2310.05797, 2023
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
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
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
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
On the Intersection of Self-Correction and Trust in Language Models
S Krishna
arXiv preprint arXiv:2311.02801, 2023
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
On the Trade-offs between Adversarial Robustness and Actionable Explanations
S Krishna, C Agarwal, H Lakkaraju
arXiv preprint arXiv:2309.16452, 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
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
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