Han, Tessa

9 publications

ICLRW 2025 Building Bridges, Not Walls: Advancing Interpretability by Unifying Feature, Data, and Model Component Attribution Shichang Zhang, Tessa Han, Usha Bhalla, Himabindu Lakkaraju

UAI 2024 Characterizing Data Point Vulnerability as Average-Case Robustness Tessa Han, Suraj Srinivas, Himabindu Lakkaraju

NeurIPS 2024 MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

TMLR 2024 The Disagreement Problem in Explainable Machine Learning: A Practitioner’s Perspective Satyapriya Krishna, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, Himabindu Lakkaraju

ICMLW 2024 Towards Safe Large Language Models for Medicine Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2024 Towards Safe Large Language Models for Medicine Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2024 Towards Safe Large Language Models for Medicine Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

ICMLW 2023 Efficient Estimation of Local Robustness of Machine Learning Models Tessa Han, Suraj Srinivas, Himabindu Lakkaraju

NeurIPS 2022 Which Explanation Should I Choose? a Function Approximation Perspective to Characterizing Post Hoc Explanations Tessa Han, Suraj Srinivas, Himabindu Lakkaraju