collaborators

5 papers

cs.LG2026

TEMPO: Scaling Test-time Training for Large Reasoning Models

Qingyang Zhang, Xinke Kong, Haitao Wu +7

Test-time training (TTT) adapts model parameters on unlabeled test instances during inference time, which continuously extends capabilities beyond the reach of offline training. De…

cs.CL2026

Think Longer to Explore Deeper: Learn to Explore In-Context via Length-Incentivized Reinforcement Learning

Futing Wang, Jianhao Yan, Yun Luo +6

Achieving effective test-time scaling requires models to engage in In-Context Exploration -- the intrinsic ability to generate, verify, and refine multiple reasoning hypotheses wit…

cs.CV2025

Spotlight on Token Perception for Multimodal Reinforcement Learning

Siyuan Huang, Xiaoye Qu, Yafu Li +4

While Reinforcement Learning with Verifiable Rewards (RLVR) has advanced the reasoning capabilities of Large Vision-Language Models (LVLMs), most existing methods in multimodal rea…

cs.CL2025

Towards an AI Musician: Synthesizing Sheet Music Problems for Musical Reasoning

Zhilin Wang, Zhe Yang, Yun Luo +8

Enhancing the ability of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) to interpret sheet music is a crucial step toward building AI musicians. However,…

cs.AI2025

HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?

Fangchen Yu, Haiyuan Wan, Qianjia Cheng +14

Recently, the physical capabilities of (M)LLMs have garnered increasing attention. However, existing benchmarks for physics suffer from two major gaps: they neither provide systema…