Valerie Chen

According to our database, Valerie Chen authored at least 23 papers between 2019 and 2024.

Collaborative distances:

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

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

Need Help? Designing Proactive AI Assistants for Programming.

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

CoRR, 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

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

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

AdvisingNets: Learning to Distinguish Correct and Wrong Classifications via Nearest-Neighbor Explanations.

Giang Nguyen, Valerie Chen, Anh Nguyen

CoRR, 2023

Learning Personalized Decision Support Policies.

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

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

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

Interpretable Machine Learning: Moving from mythos to diagnostics.

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

ACM Queue, 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