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.

My research interests lies in the intersection of NLP and AI with focus on high expertise domains like science, health-care and law. I'm currently working on building more reliable LLMs through improving their abstention ability. Previously I also worked on vision&language and explainability.

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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
Preprint

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

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
Preprint

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

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

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

ExpScore: Learning metrics for recommendation explanation

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

• 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 .