collaborators

5 papers

cs.CV2026

Democratizing the medieval English legal tradition

Michael Zhang, Elise Wang, Charlotte Whatley +2

The record of the beginning of the most widespread legal system in the world is contained in millions of pages of handwritten text. Most of the records of the first centuries of th…

cs.CL2026

Diverging Preferences: When do Annotators Disagree and do Models Know?

Michael JQ Zhang, Zhilin Wang, Jena D. Hwang +6

We examine diverging preferences in human-labeled preference datasets. We develop a taxonomy of disagreement sources spanning ten categories across four high-level classes and find…

cs.CL2025

User Feedback in Human-LLM Dialogues: A Lens to Understand Users But Noisy as a Learning Signal

Yuhan Liu, Michael J. Q. Zhang, Eunsol Choi

Once language models (LMs) are deployed, they can interact with users long-term, ideally evolving based on their feedback. Asking for direct user feedback can be disruptive; thus,…

cs.CL2025

Improving LLM-as-a-Judge Inference with the Judgment Distribution

Victor Wang, Michael J. Q. Zhang, Eunsol Choi

Using language models to scalably approximate human preferences on text quality (LLM-as-a-judge) has become a standard practice applicable to many tasks. A judgment is often extrac…

cs.CL2025

Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions

Michael J. Q. Zhang, W. Bradley Knox, Eunsol Choi

Large language models (LLMs) must often respond to highly ambiguous user requests. In such cases, the LLM's best response may be to ask a clarifying question to elicit more informa…