5 papers
EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports
Jianzhe Ma, Zhonghao Cao, Shangkui Chen +3
While video large language models (Video-LLMs) excel in understanding slow-paced, real-world egocentric videos, their capabilities in high-velocity, information-dense virtual envir…
Monitorability as a Free Gift: How RLVR Spontaneously Aligns Reasoning
Zidi Xiong, Shan Chen, Himabindu Lakkaraju
As Large Reasoning Models (LRMs) are increasingly deployed, auditing their chain-of-thought (CoT) traces for safety becomes critical. Recent work has reported that monitorability--…
Proof of Time: A Benchmark for Evaluating Scientific Idea Judgments
Bingyang Ye, Shan Chen, Jingxuan Tu +4
Large language models are increasingly being used to assess and forecast research ideas, yet we lack scalable ways to evaluate the quality of models' judgments about these scientif…
When Models Reason in Your Language: Controlling Thinking Language Comes at the Cost of Accuracy
Jirui Qi, Shan Chen, Zidi Xiong +3
Recent Large Reasoning Models (LRMs) with thinking traces have shown strong performance on English reasoning tasks. However, their ability to think in other languages is less studi…
Measuring the Faithfulness of Thinking Drafts in Large Reasoning Models
Zidi Xiong, Shan Chen, Zhenting Qi +1
Large Reasoning Models (LRMs) have significantly enhanced their capabilities in complex problem-solving by introducing a thinking draft that enables multi-path Chain-of-Thought exp…