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cs.AI2025
Deep Research Comparator: A Platform For Fine-grained Human Annotations of Deep Research Agents
Prahaladh Chandrahasan, Jiahe Jin, Zhihan Zhang +9
Effectively evaluating deep research agents that autonomously search the web, analyze information, and generate reports remains a major challenge, particularly when it comes to ass…
cs.LG2025
AutoRule: Reasoning Chain-of-thought Extracted Rule-based Rewards Improve Preference Learning
Tevin Wang, Chenyan Xiong
Rule-based rewards offer a promising strategy for improving reinforcement learning from human feedback (RLHF), but current approaches often rely on manual rule engineering. We pres…
cs.CL2025★ 2 cited
Understand User Opinions of Large Language Models via LLM-Powered In-the-Moment User Experience Interviews
Mengqiao Liu, Tevin Wang, Cassandra A. Cohen +2
Which large language model (LLM) is better? Every evaluation tells a story, but what do users really think about current LLMs? This paper presents CLUE, an LLM-powered interviewer…