Satyapriya Krishna

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 35

Top Topics

Text Classification

Machine Learning

Top Venues

Publications

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, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell
Black-Box Access is Insufficient for Rigorous AI Audits. FAccT (2024)
Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas Alexander Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell
Black-Box Access is Insufficient for Rigorous AI Audits. CoRR (2024)
Satyapriya Krishna, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, Himabindu Lakkaraju
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. Trans. Mach. Learn. Res. 2024 (2024)
Aaron J. Li, Satyapriya Krishna, Himabindu Lakkaraju
More RLHF, More Trust? On The Impact of Human Preference Alignment On Language Model Trustworthiness. CoRR (2024)
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, Jan Kocon, Bartlomiej Koptyra, Satyapriya Krishna, Ronald McClelland Jr., Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Stanislaw Wozniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence. CoRR (2024)
Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
Understanding the Effects of Iterative Prompting on Truthfulness. CoRR (2024)
Apurv Verma, Satyapriya Krishna, Sebastian Gehrmann, Madhavan Seshadri, Anu Pradhan, Tom Ault, Leslie Barrett, David Rabinowitz, John A. Doucette, NhatHai Phan
Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs). CoRR (2024)
Nicholas Kroeger, Dan Ley, Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
Are Large Language Models Post Hoc Explainers? CoRR (2023)
Satyapriya Krishna, Jiaqi Ma, Himabindu Lakkaraju
Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten. ICML (2023)
Satyapriya Krishna, Jiaqi Ma, Himabindu Lakkaraju
Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten. CoRR (2023)
Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju
Post Hoc Explanations of Language Models Can Improve Language Models. NeurIPS (2023)
Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
On the Trade-offs between Adversarial Robustness and Actionable Explanations. CoRR (2023)
Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju, Sameer Singh
Explaining machine learning models with interactive natural language conversations using TalkToModel. Nat. Mac. Intell. 5 (8) (2023)
Satyapriya Krishna
On the Intersection of Self-Correction and Trust in Language Models. CoRR (2023)
Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju
Post Hoc Explanations of Language Models Can Improve Language Models. CoRR (2023)
Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. ACL (Findings) (2022)
Chirag Agarwal, Eshika Saxena, Satyapriya Krishna, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
OpenXAI: Towards a Transparent Evaluation of Model Explanations. CoRR (2022)
Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, Himabindu Lakkaraju
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. CoRR (2022)
Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. CoRR (2022)
Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
OpenXAI: Towards a Transparent Evaluation of Model Explanations. NeurIPS (2022)
Satyapriya Krishna, Rahul Gupta, Apurv Verma, Jwala Dhamala, Yada Pruksachatkun, Kai-Wei Chang
Measuring Fairness of Text Classifiers via Prediction Sensitivity. CoRR (2022)
Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju
Rethinking Stability for Attribution-based Explanations. CoRR (2022)
Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju, Sameer Singh
TalkToModel: Understanding Machine Learning Models With Open Ended Dialogues. CoRR (2022)
Satyapriya Krishna, Rahul Gupta, Apurv Verma, Jwala Dhamala, Yada Pruksachatkun, Kai-Wei Chang
Measuring Fairness of Text Classifiers via Prediction Sensitivity. ACL (1) (2022)
Michiel de Jong, Satyapriya Krishna, Anuva Agarwal
Grounding Complex Navigational Instructions Using Scene Graphs. CoRR (2021)
Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, Kai-Wei Chang
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification. CoRR (2021)
Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta
Towards Realistic Single-Task Continuous Learning Research for NER. EMNLP (Findings) (2021)
Satyapriya Krishna, Rahul Gupta, Christophe Dupuy
ADePT: Auto-encoder based Differentially Private Text Transformation. CoRR (2021)
Satyapriya Krishna, Rahul Gupta, Christophe Dupuy
ADePT: Auto-encoder based Differentially Private Text Transformation. EACL (2021)
Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation. FAccT (2021)
Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta
Towards Realistic Single-Task Continuous Learning Research for NER. CoRR (2021)
Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation. CoRR (2021)
Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, Kai-Wei Chang
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification. ACL/IJCNLP (Findings) (2021)
Aarsh Patel, Rahul Gupta, Mukund Harakere, Satyapriya Krishna, Aman Alok, Peng Liu
Towards classification parity across cohorts. CoRR (2020)
Yunzhe Tao, Saurabh Gupta, Satyapriya Krishna, Xiong Zhou, Orchid Majumder, Vineet Khare
FineText: Text Classification via Attention-based Language Model Fine-tuning. CoRR (2019)