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2020 – today
- 2025
[i7]Shichang Zhang, Tessa Han, Usha Bhalla, Hima Lakkaraju:
Building Bridges, Not Walls - Advancing Interpretability by Unifying Feature, Data, and Model Component Attribution. CoRR abs/2501.18887 (2025)- 2024
- [j1]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) - [c4]Hongjin Lin
, Tessa Han, Krzysztof Z. Gajos, Anoopum S. Gupta:
Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support. ASSETS 2024: 79:1-79:10 - [c3]Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju:
MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models. NeurIPS 2024 - [c2]Tessa Han, Suraj Srinivas, Himabindu Lakkaraju:
Characterizing Data Point Vulnerability as Average-Case Robustness. UAI 2024: 1513-1540 - [i6]Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju:
Towards Safe and Aligned Large Language Models for Medicine. CoRR abs/2403.03744 (2024) - [i5]Hongjin Lin, Tessa Han, Krzysztof Z. Gajos, Anoopum S. Gupta:
Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support. CoRR abs/2409.06088 (2024) - 2023
- [i4]Tessa Han, Suraj Srinivas, Himabindu Lakkaraju:
Efficient Estimation of the Local Robustness of Machine Learning Models. CoRR abs/2307.13885 (2023) - [i3]Tessa Han, Yasha Ektefaie, Maha R. Farhat, Marinka Zitnik, Himabindu Lakkaraju:
Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts. CoRR abs/2312.05690 (2023) - 2022
- [c1]Tessa Han, Suraj Srinivas, Himabindu Lakkaraju:
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations. NeurIPS 2022 - [i2]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 abs/2202.01602 (2022) - [i1]Tessa Han, Suraj Srinivas, Himabindu Lakkaraju:
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations. CoRR abs/2206.01254 (2022)
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