Novelty Detection via Network Saliency in Visual-Based Deep Learning. - Valerie Chen; Man-Ki Yoon; Zhong Shao 001 (DSN Workshops, 2019)

Video-Text Compliance: Activity Verification Based on Natural Language Instructions. - Mayoore Jaiswal; H. Peter Hofstee; Valerie Chen; Suvadip Paul; Rogério Feris; Frank Liu 001; Anupama Jagannathan; Anne Gattiker; Inseok Hwang 001; Jinho Lee; Matthew Tong; Sahil Dureja; et al. (ICCV Workshops, 2019)

Secure Computation for Machine Learning With SPDZ. - Valerie Chen; Valerio Pastro; Mariana Raykova 001 (CoRR, 2019)

Task-Aware Novelty Detection for Visual-based Deep Learning in Autonomous Systems. - Valerie Chen; Man-Ki Yoon; Zhong Shao 001 (ICRA, 2020)

Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning. - Valerie Chen; Abhinav Gupta 001; Kenneth Marino (ICLR, 2021)

Towards Connecting Use Cases and Methods in Interpretable Machine Learning. - Valerie Chen; Jeffrey Li; Joon Sik Kim; Gregory Plumb; Ameet Talwalkar (CoRR, 2021)

Interpretable Machine Learning: Moving from mythos to diagnostics. - Valerie Chen; Jeffrey Li; Joon Sik Kim; Gregory Plumb; Ameet Talwalkar (ACM Queue, 2021)

Use-Case-Grounded Simulations for Explanation Evaluation. - Valerie Chen; Nari Johnson; Nicholay Topin; Gregory Plumb; Ameet Talwalkar (NeurIPS, 2022)

Bayesian Persuasion for Algorithmic Recourse. - Keegan Harris; Valerie Chen; Joon Sik Kim; Ameet Talwalkar; Hoda Heidari; Zhiwei Steven Wu (NeurIPS, 2022)

Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions. - Valerie Chen (AIES, 2023)

FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines. - Matthew Barker; Emma Kallina; Dhananjay Ashok; Katherine M. Collins; Ashley Casovan; Adrian Weller; Ameet Talwalkar; Valerie Chen; Umang Bhatt (EAAMO, 2023)

A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies. - Ada Martin; Valerie Chen; Sérgio M. Jesus; Pedro Saleiro (CoRR, 2023)

Do LLMs exhibit human-like response biases? A case study in survey design. - Lindia Tjuatja; Valerie Chen; Sherry Tongshuang Wu; Ameet Talwalkar; Graham Neubig (CoRR, 2023)

Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations. - Valerie Chen; Q. Vera Liao; Jennifer Wortman Vaughan; Gagan Bansal (Proc. ACM Hum. Comput. Interact., 2023)

Assisting Human Decisions in Document Matching. - Joon Sik Kim; Valerie Chen; Danish Pruthi; Nihar B. Shah; Ameet Talwalkar (Trans. Mach. Learn. Res., 2023)

Perspectives on incorporating expert feedback into model updates. - Valerie Chen; Umang Bhatt; Hoda Heidari; Adrian Weller; Ameet Talwalkar (Patterns, 2023)

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods. - Kasun Amarasinghe; Kit T. Rodolfa; Sérgio M. Jesus; Valerie Chen; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro; Ameet Talwalkar; Rayid Ghani (AAAI, 2024)

Modulating Language Model Experiences through Frictions. - Katherine M. Collins; Valerie Chen; Ilia Sucholutsky; Hannah Rose Kirk; Malak Sadek; Holli Sargeant; Ameet Talwalkar; Adrian Weller; Umang Bhatt (CoRR, 2024)

Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design. - Lindia Tjuatja; Valerie Chen; Tongshuang Wu; Ameet Talwalkwar; Graham Neubig (Trans. Assoc. Comput. Linguistics, 2024)

PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans. - Giang (Dexter) Nguyen; Valerie Chen; Mohammad Reza Taesiri; Anh Totti Nguyen (Trans. Mach. Learn. Res., 2024)

Learning Personalized Decision Support Policies. - Umang Bhatt; Valerie Chen; Katherine M. Collins; Parameswaran Kamalaruban; Emma Kallina; Adrian Weller; Ameet Talwalkar (AAAI, 2025)

When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback. - Jane Pan; Ryan Shar; Jacob Pfau; Ameet Talwalkar; He He 001; Valerie Chen (ACL (Findings), 2025)

Need Help? Designing Proactive AI Assistants for Programming. - Valerie Chen; Alan Zhu 003; Sebastian Zhao; Hussein Mozannar; David A. Sontag; Ameet Talwalkar (CHI, 2025)

CodingGenie: A Proactive LLM-Powered Programming Assistant. - Sebastian Zhao; Alan Zhu 003; Hussein Mozannar; David A. Sontag; Ameet Talwalkar; Valerie Chen (SIGSOFT FSE Companion, 2025)

The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers. - Hussein Mozannar; Valerie Chen; Mohammed Alsobay; Subhro Das; Sebastian Zhao; Dennis Wei; Manish Nagireddy; Prasanna Sattigeri; Ameet Talwalkar; David A. Sontag (Trans. Mach. Learn. Res., 2025)

Copilot Arena: A Platform for Code LLM Evaluation in the Wild. - Wayne Chi; Valerie Chen; Anastasios Nikolas Angelopoulos; Wei-Lin Chiang; Aditya Mittal; Naman Jain; Tianjun Zhang; Ion Stoica; Chris Donahue; Ameet Talwalkar (CoRR, 2025)

Beyond Memorization: Mapping the Originality-Quality Frontier of Language Models. - Vishakh Padmakumar; Chen Yueh-Han; Jane Pan; Valerie Chen; He He 001 (CoRR, 2025)

Coding Agents with Multimodal Browsing are Generalist Problem Solvers. - Aditya Bharat Soni; Boxuan Li; Xingyao Wang 002; Valerie Chen; Graham Neubig (CoRR, 2025)

Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows. - Valerie Chen; Ameet Talwalkar; Robert Brennan; Graham Neubig (CoRR, 2025)

Why Do Decision Makers (Not) Use AI? A Cross-Domain Analysis of Factors Impacting AI Adoption. - Rebecca Yu; Valerie Chen; Ameet Talwalkar; Hoda Heidari (CoRR, 2025)