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


The Critical Role of Abstention in Building Reliable Large Language Model
Ongoing survey paper


Benchmarking LLM's Information Extraction Ability on Legal Documents
Ongoing project


Retrieval-augmented Instruction Tuning for User-defined Tasks
Ongoing project


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

  • NeuraIPS: 2023
  • ICLR: 2023/2024
  • ACL: 2024
  • EMNLP: 2022/2023
  • AAAI: 2024

A special thanks to Yujie Li .