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20242026
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cs.CL2026

Gavel: Agent Meets Checklist for Evaluating LLMs on Long-Context Legal Summarization

Yao Dou, Benjamin Mamut, Wei Xu

Large language models (LLMs) now support contexts of up to 1M tokens, but their strengths and weaknesses on complex long-context tasks remain unclear. To study this, we focus on mu…

cs.CL2026

Localizing Prompt Ambiguity in Large Language Models with Probe-Targeted Attribution

Govind Ramesh, Yao Dou, Wei Xu

Prompt ambiguity is a common source of failure in large language models, but is difficult to localize because it is a latent property of the prompt, while existing attribution meth…

cs.CL2025

SimulatorArena: Are User Simulators Reliable Proxies for Multi-Turn Evaluation of AI Assistants?

Yao Dou, Michel Galley, Baolin Peng +6

Large language models (LLMs) are increasingly used in interactive applications, and human evaluation remains the gold standard for assessing their performance in multi-turn convers…

cs.CL2024

Towards Reliable Detection of LLM-Generated Texts: A Comprehensive Evaluation Framework with CUDRT

Zhen Tao, Yanfang Chen, Dinghao Xi +2

The increasing prevalence of large language models (LLMs) has significantly advanced text generation, but the human-like quality of LLM outputs presents major challenges in reliabl…

cs.CL2024

Improving Minimum Bayes Risk Decoding with Multi-Prompt

David Heineman, Yao Dou, Wei Xu

While instruction fine-tuned LLMs are effective text generators, sensitivity to prompt construction makes performance unstable and sub-optimal in practice. Relying on a single "bes…

cs.CL2024

Reducing Privacy Risks in Online Self-Disclosures with Language Models

Yao Dou, Isadora Krsek, Tarek Naous +4

Self-disclosure, while being common and rewarding in social media interaction, also poses privacy risks. In this paper, we take the initiative to protect the user-side privacy asso…