Hello World!
I'm Sherry Tongshuang Wu
(吴彤霜)!
Assistant Professor
School of CS, Carnegie Mellon University (CMU SCS)
Human Computer Interaction Institute (HCII)
Language Technololgy Institute (LTI)

I am trained (by my amazing PhD advisors Jeffrey Heer and Dan Weld at the University of Washington) to be an HCI+NLP researcher. I study how humans (AI experts, lay users, domain experts) interact with (debug, audit, collaborate) AI systems.

Most recently, I work on:

Build practical AI systems, by mapping general-purpose AIs to the right specific use cases.

Click & jump to some recent papers that represent my research interests and style:
If you are interested in exploring relevant topics with me at CMU, I will be looking for undergraduate, master or PhD students! PLEASE read this FAQ to find out our open projects and best ways to contact us.

Research Highlights

Real-world AI Evaluation
Beyond Relevance: Evaluate and Improve Retrievers on Perspective Awareness
Xinran Zhao, Tong Chen, Sihao Chen, Hongming Zhang, Tongshuang Wu
CoLM 2024: Conference on Language Modeling
Orbit: A Framework for Designing and Evaluating Multi-objective Rankers
Chenyang Yang, Yining Hong, Grace A. Lewis, Tongshuang Wu, Christian Kästner
ASE 2024: the 39th IEEE/ACM International Conference on Automated Software Engineering
What Is Wrong with My Model? Identifying Systematic Problems with Semantic Data Slicing
Chenyang Yang, Yining Hong, Grace A. Lewis, Tongshuang Wu, Christian Kästner
ASE 2024: the 39th IEEE/ACM International Conference on Automated Software Engineering
LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs
Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Bill Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang
ArXiv 2024: ArXiv
Task-specific AI Test & Distill.
Beyond Testers' Biases: Guiding Model Testing with Knowledge Bases using LLMs
Chenyang Yang, Rishabh Rustogi, Rachel Brower-Sinning, Grace Lewis, Christian Kaestner, Tongshuang Wu
EMNLP Findings 2023: The 2023 Conference on Empirical Methods in Natural Language Processing
Promp2Model: Generating Deployable Models from Natural Language Instructions
Vijay Viswanathan, Chenyang Zhao, Amanda Bertsch, Tongshuang Wu, Graham Neubig
EMNLP Demo Track 2023: The 2023 Conference on Empirical Methods in Natural Language Processing
Human-AI Task Delegation
Is AI the Better Programming Partner? Human-Human Pair Programming vs. Human-AI pAIr Programming
Qianou Christina Ma, Tongshuang Wu, Kenneth Koedinger
AIED2023 Empowering Education with LLMs 2023: AIED2023 Empowering Education with LLMs - the Next-Gen Interface and Content Generation
How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debugging Best Paper
Qiaomu Ma, Hua Shen, Kenneth Koedinger, Tongshuang Wu
AIED 2024: The 25th International Conference on Artificial Intelligence in Education
What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use
Qianou Ma, Weirui Peng, Hua Shen, Kenneth Koedinger, Tongshuang Wu
ArXiv 2024: ArXiv 2409.08775