Pan, Weiwei

32 publications

ICLRW 2025 AI Companions Are Not the Solution to Loneliness: Design Choices and Their Drawbacks Jonas B Raedler, Siddharth Swaroop, Weiwei Pan

TMLR 2025 Is What You Ask for What You Get? Investigating Concept Associations in Text-to-Image Models Salma Abdel Magid, Weiwei Pan, Simon Warchol, Grace Guo, Junsik Kim, Mahia Rahman, Hanspeter Pfister

ICML 2025 Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan

ICLRW 2025 Rethinking LLM Bias Probing Using Lessons from the Social Sciences Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan

UAI 2025 Transparent Trade-Offs Between Properties of Explanations Hiwot Belay Tadesse, Alihan Hüyük, Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez

ICMLW 2024 A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning Eura Nofshin, Esther Brown, Brian Lim, Weiwei Pan, Finale Doshi-Velez

ICMLW 2024 AMBER: An Entropy Maximizing Environment Design Algorithm for Inverse Reinforcement Learning Paul Nitschke, Lars Lien Ankile, Eura Nofshin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan

NeurIPSW 2024 Accuracy Isn’t Everything: Understanding the Desiderata of AI Tools in Legal-Financial Settings Sudhan Chitgopkar, Noah Dohrmann, Stephanie Monson, Jimmy Mendez, Finale Doshi-Velez, Weiwei Pan

NeurIPSW 2024 An Autonomy-Based Classification: Liability in the Age of AI Agents Julia Smakman, Lisa Soder, Connor Dunlop, Weiwei Pan, Siddharth Swaroop

ICMLW 2024 Bias Transmission in Large Language Models: Evidence from Gender-Occupation Bias in GPT-4 Kirsten Morehouse, Weiwei Pan, Juan Manuel Contreras, Mahzarin R. Banaji

NeurIPSW 2024 Is What You Ask for What You Get? Investigating Concept Associations in Text-to-Image Models Salma Abdel Magid, Weiwei Pan, Simon Warchol, Grace Guo, Junsik Kim, Wanhua Li, Mahia Rahman, Hanspeter Pfister

NeurIPSW 2024 Levels of Autonomy: Liability in the Age of AI Agents Lisa Soder, Julia Smakman, Connor Dunlop, Weiwei Pan, Siddharth Swaroop, Noam Kolt

NeurIPSW 2024 Position: AI Agents & Liability – Mapping Insights from ML and HCI Research to Policy Connor Dunlop, Weiwei Pan, Julia Smakman, Lisa Soder, Siddharth Swaroop

JMLR 2024 Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning Sarah Rathnam, Sonali Parbhoo, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez

ICMLW 2024 Synthetic Data-Driven Prediction of Height for Childhood Malnutrition David Berthiaume, Yuan Tang, Chau Nguyen, Siyu Gai, Emilia Mazzolenis, Weiwei Pan

NeurIPSW 2024 Understanding Model Bias Requires Systematic Probing Across Tasks Soline Boussard, Susannah Cheng Su, Helen Zhao, Siddharth Swaroop, Weiwei Pan

ICMLW 2024 Using Large Language Models for Humanitarian Frontline Negotiation: Opportunities and Considerations Zilin Ma, Susannah Cheng Su, Nathan Zhao, Linn Bieske, Blake Bullwinkel, Yanyi Zhang, Jinglun Gao, Gekai Liao, Siyao Li, Ziqing Luo, Boxiang Wang, Zihan Wen, Yanrui Yang, Claude Bruderlein, Weiwei Pan

ICMLW 2023 Discovering User Types: Characterization of User Traits by Task-Specific Behaviors in Reinforcement Learning Lars Lien Ankile, Brian Ham, Kevin Mao, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan

ICMLW 2023 Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning Lars Lien Ankile, Brian Ham, Kevin Mao, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan

ICMLW 2023 Signature Activation: A Sparse Signal View for Holistic Saliency Jose Roberto Tello Ayala, Akl C. Fahed, Weiwei Pan, Eugene V. Pomerantsev, Patrick Thomas Ellinor, Anthony Philippakis, Finale Doshi-Velez

ICMLW 2023 Soft Prompting Might Be a Bug, Not a Feature Luke Bailey, Gustaf Ahdritz, Anat Kleiman, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan

ICML 2023 The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan Murphy, Finale Doshi-Velez

ICMLW 2023 Why Do Universal Adversarial Attacks Work on Large Language Models?: Geometry Might Be the Answer Varshini Subhash, Anna Bialas, Weiwei Pan, Finale Doshi-Velez

AISTATS 2022 Wide Mean-Field Bayesian Neural Networks Ignore the Data Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez

NeurIPSW 2022 An Empirical Analysis of the Advantages of Finite V.s. Infinite Width Bayesian Neural Networks Jiayu Yao, Yaniv Yacoby, Beau Coker, Weiwei Pan, Finale Doshi-Velez

JMLR 2022 Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez

NeurIPSW 2022 What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Varshini Subhash, Zixi Chen, Marton Havasi, Weiwei Pan, Finale Doshi-Velez

NeurIPSW 2022 What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez

UAI 2021 Efficient Online Inference for Nonparametric Mixture Models Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Rani Fiete

MLHC 2021 Power Constrained Bandits Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan Murphy, Finale Doshi-Velez

AAAI 2020 Ensembles of Locally Independent Prediction Models Andrew Slavin Ross, Weiwei Pan, Leo A. Celi, Finale Doshi-Velez

AISTATS 2018 Weighted Tensor Decomposition for Learning Latent Variables with Partial Data Omer Gottesman, Weiwei Pan, Finale Doshi-Velez