Tessa Han

According to our database, Tessa Han authored at least 10 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Building Bridges, Not Walls - Advancing Interpretability by Unifying Feature, Data, and Model Component Attribution.

Shichang Zhang, Tessa Han, Usha Bhalla, Hima Lakkaraju

CoRR, January, 2025

2024

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.

Satyapriya Krishna, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, Himabindu Lakkaraju

Trans. Mach. Learn. Res., 2024

Towards Safe and Aligned Large Language Models for Medicine.

Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

CoRR, 2024

Characterizing Data Point Vulnerability as Average-Case Robustness.

Tessa Han, Suraj Srinivas, Himabindu Lakkaraju

Proceedings of the Uncertainty in Artificial Intelligence, 2024

MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models.

Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support.

Hongjin Lin, Tessa Han, Krzysztof Z. Gajos, Anoopum S. Gupta

Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility, 2024

2023

Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts.

Tessa Han, Yasha Ektefaie, Maha R. Farhat, Marinka Zitnik, Himabindu Lakkaraju

CoRR, 2023

Efficient Estimation of the Local Robustness of Machine Learning Models.

Tessa Han, Suraj Srinivas, Himabindu Lakkaraju

CoRR, 2023

2022

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.

Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, Himabindu Lakkaraju

CoRR, 2022

Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations.

Tessa Han, Suraj Srinivas, Himabindu Lakkaraju

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022