FineText: Text Classification via Attention-based Language Model Fine-tuning. - Yunzhe Tao; Saurabh Gupta; Satyapriya Krishna; Xiong Zhou; Orchid Majumder; Vineet Khare (CoRR, 2019)

Towards classification parity across cohorts. - Aarsh Patel; Rahul Gupta 001; Mukund Harakere; Satyapriya Krishna; Aman Alok; Peng Liu (CoRR, 2020)

Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification. - Yada Pruksachatkun; Satyapriya Krishna; Jwala Dhamala; Rahul Gupta 001; Kai-Wei Chang (ACL/IJCNLP (Findings), 2021)

ADePT: Auto-encoder based Differentially Private Text Transformation. - Satyapriya Krishna; Rahul Gupta 001; Christophe Dupuy (EACL, 2021)

Towards Realistic Single-Task Continuous Learning Research for NER. - Justin Payan; Yuval Merhav; He Xie; Satyapriya Krishna; Anil Ramakrishna; Mukund Sridhar; Rahul Gupta 001 (EMNLP (Findings), 2021)

BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation. - Jwala Dhamala; Tony Sun; Varun Kumar; Satyapriya Krishna; Yada Pruksachatkun; Kai-Wei Chang; Rahul Gupta 001 (FAccT, 2021)

Grounding Complex Navigational Instructions Using Scene Graphs. - Michiel de Jong; Satyapriya Krishna; Anuva Agarwal (CoRR, 2021)

Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. - Umang Gupta; Jwala Dhamala; Varun Kumar; Apurv Verma; Yada Pruksachatkun; Satyapriya Krishna; Rahul Gupta 001; Kai-Wei Chang; Greg Ver Steeg; Aram Galstyan (ACL (Findings), 2022)

Measuring Fairness of Text Classifiers via Prediction Sensitivity. - Satyapriya Krishna; Rahul Gupta 001; Apurv Verma; Jwala Dhamala; Yada Pruksachatkun; Kai-Wei Chang (ACL (1), 2022)

OpenXAI: Towards a Transparent Evaluation of Model Explanations. - Chirag Agarwal; Satyapriya Krishna; Eshika Saxena; Martin Pawelczyk; Nari Johnson; Isha Puri; Marinka Zitnik; Himabindu Lakkaraju (NeurIPS, 2022)

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. - Satyapriya Krishna; Tessa Han; Alex Gu; Javin Pombra; Shahin Jabbari; Steven Wu 001; Himabindu Lakkaraju (CoRR, 2022)

Rethinking Stability for Attribution-based Explanations. - Chirag Agarwal; Nari Johnson; Martin Pawelczyk; Satyapriya Krishna; Eshika Saxena; Marinka Zitnik; Himabindu Lakkaraju (CoRR, 2022)

TalkToModel: Understanding Machine Learning Models With Open Ended Dialogues. - Dylan Slack; Satyapriya Krishna; Himabindu Lakkaraju; Sameer Singh 001 (CoRR, 2022)

Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten. - Satyapriya Krishna; Jiaqi Ma 004; Himabindu Lakkaraju (ICML, 2023)

Post Hoc Explanations of Language Models Can Improve Language Models. - Satyapriya Krishna; Jiaqi Ma 004; Dylan Slack; Asma Ghandeharioun; Sameer Singh 001; Himabindu Lakkaraju (NeurIPS, 2023)

Are Large Language Models Post Hoc Explainers? - Nicholas Kroeger; Dan Ley; Satyapriya Krishna; Chirag Agarwal; Himabindu Lakkaraju (CoRR, 2023)

On the Intersection of Self-Correction and Trust in Language Models. - Satyapriya Krishna (CoRR, 2023)

Explaining machine learning models with interactive natural language conversations using TalkToModel. - Dylan Slack; Satyapriya Krishna; Himabindu Lakkaraju; Sameer Singh 001 (Nat. Mac. Intell., 2023)

On the Trade-offs between Adversarial Robustness and Actionable Explanations. - Satyapriya Krishna; Chirag Agarwal; Himabindu Lakkaraju (AIES (1), 2024)

Black-Box Access is Insufficient for Rigorous AI Audits. - Stephen Casper; Carson Ezell; Charlotte Siegmann; Noam Kolt; Taylor Lynn Curtis; Benjamin Bucknall; Andreas A. Haupt; Kevin Wei; Jérémy Scheurer; Marius Hobbhahn; Lee Sharkey; Satyapriya Krishna; et al. (FAccT, 2024)

Understanding the Effects of Iterative Prompting on Truthfulness. - Satyapriya Krishna; Chirag Agarwal; Himabindu Lakkaraju (ICML, 2024)

Croissant: A Metadata Format for ML-Ready Datasets. - Mubashara Akhtar; Omar Benjelloun; Costanza Conforti; Luca Foschini 002; Joan Giner-Miguelez; Pieter Gijsbers; Sujata S. Goswami; Nitisha Jain; Michalis Karamousadakis; Michael Kuchnik; Satyapriya Krishna; Sylvain Lesage; et al. (NeurIPS, 2024)

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence. - Bo Peng; Daniel Goldstein; Quentin Anthony; Alon Albalak; Eric Alcaide; Stella Biderman; Eugene Cheah; Xingjian Du; Teddy Ferdinan; Haowen Hou; Przemyslaw Kazienko; Kranthi Kiran GV; et al. (CoRR, 2024)

More RLHF, More Trust? On The Impact of Human Preference Alignment On Language Model Trustworthiness. - Aaron Jiaxun Li; Satyapriya Krishna; Himabindu Lakkaraju (CoRR, 2024)

Insights from the Inverse: Reconstructing LLM Training Goals Through Inverse RL. - Jared Joselowitz; Arjun Jagota; Satyapriya Krishna; Sonali Parbhoo (CoRR, 2024)

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. - Satyapriya Krishna; Tessa Han; Alex Gu; Steven Wu 001; Shahin Jabbari; Himabindu Lakkaraju (Trans. Mach. Learn. Res., 2024)

More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness. - Aaron Jiaxun Li; Satyapriya Krishna; Himabindu Lakkaraju (ICLR, 2025)

Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation. - Satyapriya Krishna; Kalpesh Krishna; Anhad Mohananey; Steven Schwarcz; Adam Stambler; Shyam Upadhyay; Manaal Faruqui (NAACL (Long Papers), 2025)

Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs). - Apurv Verma; Satyapriya Krishna; Sebastian Gehrmann; Madhavan Seshadri; Anu Pradhan; John A. Doucette; David Rabinowitz; Leslie Barrett; Tom Ault; Hai Phan 001 (Trans. Mach. Learn. Res., 2025)

AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. - Shaona Ghosh; Heather Frase; Adina Williams; Sarah Luger; Paul Röttger; Fazl Barez; Sean McGregor; Kenneth Fricklas; Mala Kumar; Quentin Feuillade-Montixi; Kurt Bollacker; Felix Friedrich; et al. (CoRR, 2025)

Evaluating the Critical Risks of Amazon's Nova Premier under the Frontier Model Safety Framework. - Satyapriya Krishna; Ninareh Mehrabi; Abhinav Mohanty; Matteo Memelli; Vincent Ponzo; Payal Motwani; Rahul Gupta 001 (CoRR, 2025)