Bingbing Wen

I am a PhD student at University of Washington. I'm fortunate to be advised by Prof. Bill Howe and Prof. Lucy Lu Wang. I also work closely with Prof. Yulia Tsvetkov. I'm a member of UW RAISE Center and The AI Clinic

My research focuses on building trustworthy foundation models. I work on three areas: data curation and synthesis for high-quality pretraining and posttraining, model efficient training such as mixture-of-LoRA experts and reinforcement learning, and human-aligned evaluation.

During my PhD, I had the opportunity to conduct research internships at Apple, Microsoft Cloud AI, and OPPO Research, where I explored challenges in building large-scale AI systems. I also collaborate closely with the Allen Institute for AI.

I actively mentor undergraduate and master students in developing and carrying out research projects--feel free to reach out if you're interested in my research or phd application.

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News
Selected Publications
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MARVEL: Modular Abstention for Reliable and Versatile Expert LLMs
Bingbing Wen, Faeze Brahman, Zhan Su , Shangbin Feng, Yulia Tsvetkov, Lucy Lu Wang, Bill Howe
ICML Reliable Foundation Model Workshop & NeurIPS Submission

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Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs
Chenjun Xu*, Bingbing Wen*, Bin Han, Robert Wolfe, Lucy Lu Wang, Bill Howe
ACL2025 findings

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Know Your Limits: A Survey of Abstention in Large Language Models
Bingbing Wen, Jihan Yao, Shangbin Feng, Chenjun Xu, Yulia Tsvetkov, Bill Howe, Lucy Lu Wang
TACL2025, ACL2025 Oral

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AutoScale-Automatic Prediction of Compute-optimal Data Composition for Training LLMs
Feiyang Kang*, Yifan Sun*, Bingbing Wen, Si Chen, Dawn Song, Rafid Mahmood, Ruoxi Jia
COLM2025

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Characterizing LLM Abstention Behavior in Science QA with Context Perturbations
Bingbing Wen, Bill Howe, Lucy Lu Wang
EMNLP2024 Findings

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InfoVisDial: An Informative Visual Dialogue Dataset by Bridging Large Multimodal and Language Models
Bingbing Wen, Zhengyuan Yang, Jianfeng Wang, Zhe Gan, Bill Howe, Lijuan Wang

Internship at Microsoft Azure AI

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CCQ: cross-class query network for partially labeled organ segmentation

Xuyang Liu*, Bingbing Wen*,Sibei Yang
AAAI, 2023

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ExpScore: Learning metrics for recommendation explanation

Bingbing Wen,Yunhe Feng, Yongfeng Zhang, Chirag Shah
WWW, 2022

Reviewing
  • NeurIPS: 2023/2024
  • NeurIPS dataset and benchmark: 2023/2024
  • ICLR: 2023/2024
  • EMNLP: 2022/2023
  • AAAI: 2024
  • WACV: 2024/2025

A special thanks to Yujie Li .