Valerie Chen

According to our database, Valerie Chen authored at least 45 papers between 2019 and 2026.

Collaborative distances:

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

2026

RECAP: An End-to-End Platform for Capturing, Replaying, and Analyzing AI-Assisted Programming Interactions.

Keyu He, Qianou Ma, Valerie Chen, Wayne Chi, Tongshuang Wu

CoRR, May, 2026

Comparing Developer and LLM Biases in Code Evaluation.

Aditya Mittal, Ryan Shar, Zichu Wu, Shyam Agarwal, Tongshuang Wu, Chris Donahue, Ameet Talwalkar, Wayne Chi, Valerie Chen

CoRR, March, 2026

RCTs & Human Uplift Studies: Methodological Challenges and Practical Solutions for Frontier AI Evaluation.

Patricia Paskov, Kevin Wei, Shen Zhou Hong, Dan Bateyko, Xavier Roberts-Gaal, Carson Ezell, Gailius Praninskas, Valerie Chen, Umang Bhatt, Ella Guest

CoRR, March, 2026

A Rubric-Supervised Critic from Sparse Real-World Outcomes.

Xingyao Wang, Valerie Chen, Heng Ji, Graham Neubig

CoRR, March, 2026

How Well Does Agent Development Reflect Real-World Work?

Zora Zhiruo Wang, Sanidhya Vijayvargiya, Aspen Chen, Hanmo Zhang, Venu Arvind Arangarajan, Jett Chen, Valerie Chen, Diyi Yang, Daniel Fried, Graham Neubig

CoRR, March, 2026

GameDevBench: Evaluating Agentic Capabilities Through Game Development.

Wayne Chi, Yixiong Fang, Arnav Yayavaram, Siddharth Yayavaram, Seth Karten, Qiuhong Anna Wei, Runkun Chen, Alexander Wang, Valerie Chen, Ameet Talwalkar, Chris Donahue

CoRR, February, 2026

Beyond the Commit: Developer Perspectives on Productivity with AI Coding Assistants.

Valerie Chen, Jasmyn He, Behnjamin Williams, Jason Valentino, Ameet Talwalkar

CoRR, February, 2026

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories.

Aditya Bharat Soni, Rajat Ghosh, Vaishnavi Bhargava, Valerie Chen, Debojyoti Dutta

CoRR, January, 2026

Developer Interaction Patterns with Proactive AI: A Five-Day Field Study.

Nadine Kuo, Agnia Sergeyuk, Valerie Chen, Maliheh Izadi

Proceedings of the 31st International Conference on Intelligent User Interfaces, 2026

Coding Agents with Multimodal Browsing are Generalist Problem Solvers.

Aditya Bharat Soni, Boxuan Li, Xingyao Wang, Valerie Chen, Graham Neubig

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

Third Workshop on Human-Centered Evaluation and Auditing of Language Models: AI Agents-in-the-Loop.

Willem van der Maden, Wesley Hanwen Deng, Yu Lu Liu, Han Jiang, Valerie Chen, Haotian Li, Juho Kim, Q. Vera Liao, Wei Xu, Motahhare Eslami, Ziang Xiao

Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, 2026

Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows.

Valerie Chen, Ameet Talwalkar, Robert Brennan, Graham Neubig

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, 2026

2025

EDIT-Bench: Evaluating LLM Abilities to Perform Real-World Instructed Code Edits.

Wayne Chi, Valerie Chen, Ryan Shar, Aditya Mittal, Jenny Liang, Wei-Lin Chiang, Anastasios Nikolas Angelopoulos, Ion Stoica, Graham Neubig, Ameet Talwalkar, Chris Donahue

CoRR, November, 2025

The OpenHands Software Agent SDK: A Composable and Extensible Foundation for Production Agents.

Xingyao Wang, Simon Rosenberg, Juan Michelini, Calvin Smith, Hoang H. Tran, Engel Nyst, Rohit Malhotra, Xuhui Zhou, Valerie Chen, Robert Brennan, Graham Neubig

CoRR, November, 2025

Completion ≠ Collaboration: Scaling Collaborative Effort with Agents.

Shannon Zejiang Shen, Valerie Chen, Ken Gu, Alexis Ross, Zixian Ma, Jillian Ross, Alex Gu, Chenglei Si, Wayne Chi, Andi Peng, Jocelyn J. Shen, Ameet Talwalkar, Tongshuang Wu, David A. Sontag

CoRR, October, 2025

TOM-SWE: User Mental Modeling For Software Engineering Agents.

Xuhui Zhou, Valerie Chen, Zora Zhiruo Wang, Graham Neubig, Maarten Sap, Xingyao Wang

CoRR, October, 2025

How can we assess human-agent interactions? Case studies in software agent design.

Valerie Chen, Rohit Malhotra, Xingyao Wang, Juan Michelini, Xuhui Zhou, Aditya Bharat Soni, Hoang H. Tran, Calvin Smith, Ameet Talwalkar, Graham Neubig

CoRR, October, 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, August, 2025

Beyond Memorization: Mapping the Originality-Quality Frontier of Language Models.

Vishakh Padmakumar, Yueh-Han Chen, Jane Pan, Valerie Chen, He He

CoRR, April, 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

CodingGenie: A Proactive LLM-Powered Programming Assistant.

Sebastian Zhao, Alan Zhu, Hussein Mozannar, David A. Sontag, Ameet Talwalkar, Valerie Chen

Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Need Help? Designing Proactive AI Assistants for Programming.

Valerie Chen, Alan Zhu, Sebastian Zhao, Hussein Mozannar, David A. Sontag, Ameet Talwalkar

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025

When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback.

Jane Pan, Ryan Shar, Jacob Pfau, Ameet Talwalkar, He He, Valerie Chen

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Learning Personalized Decision Support Policies.

Umang Bhatt, Valerie Chen, Katherine M. Collins, Parameswaran Kamalaruban, Emma Kallina, Adrian Weller, Ameet Talwalkar

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

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

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

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

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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Perspectives on incorporating expert feedback into model updates.

Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller, Ameet Talwalkar

Patterns, July, 2023

Assisting Human Decisions in Document Matching.

Joon Sik Kim, Valerie Chen, Danish Pruthi, Nihar B. Shah, Ameet Talwalkar

Trans. Mach. Learn. Res., 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

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

A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies.

Ada Martin, Valerie Chen, Sérgio M. Jesus, Pedro Saleiro

CoRR, 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

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions.

Valerie Chen

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Interpretable machine learning: moving from mythos to diagnostics.

Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar

Commun. ACM, 2022

Bayesian Persuasion for Algorithmic Recourse.

Keegan Harris, Valerie Chen, Joon Sik Kim, Ameet Talwalkar, Hoda Heidari, Zhiwei Steven Wu

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

Use-Case-Grounded Simulations for Explanation Evaluation.

Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar

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

2021

Towards Connecting Use Cases and Methods in Interpretable Machine Learning.

Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar

CoRR, 2021

Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning.

Valerie Chen, Abhinav Gupta, Kenneth Marino

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Task-Aware Novelty Detection for Visual-based Deep Learning in Autonomous Systems.

Valerie Chen, Man-Ki Yoon, Zhong Shao

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Secure Computation for Machine Learning With SPDZ.

Valerie Chen, Valerio Pastro, Mariana Raykova

CoRR, 2019

Video-Text Compliance: Activity Verification Based on Natural Language Instructions.

Mayoore Jaiswal, H. Peter Hofstee, Valerie Chen, Suvadip Paul, Rogério Feris, Frank Liu, Anupama Jagannathan, Anne Gattiker, Inseok Hwang, Jinho Lee, Matthew Tong, Sahil Dureja, Soham Shah

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Novelty Detection via Network Saliency in Visual-Based Deep Learning.

Valerie Chen, Man-Ki Yoon, Zhong Shao

Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2019