9 citations · 25 across the 33 of their papers we have counts for
9 papers · 1 filter
Timely Machine: Awareness of Time Makes Test-Time Scaling Agentic
Yichuan Ma, Linyang Li, Yongkang chen +5
As large language models (LLMs) increasingly tackle complex reasoning tasks, test-time scaling has become critical for enhancing capabilities. However, in agentic scenarios with fr…
TL-GRPO: Turn-Level RL for Reasoning-Guided Iterative Optimization
Peiji Li, Linyang Li, Handa Sun +15
Large language models have demonstrated strong reasoning capabilities in complex tasks through tool integration, which is typically framed as a Markov Decision Process and optimize…
Mixing Expert Knowledge: Bring Human Thoughts Back To the Game of Go
Yichuan Ma, Linyang Li, Yongkang Chen +5
Large language models (LLMs) have demonstrated exceptional performance in reasoning tasks such as mathematics and coding, matching or surpassing human capabilities. However, these…
OPV: Outcome-based Process Verifier for Efficient Long Chain-of-Thought Verification
Zijian Wu, Lingkai Kong, Wenwei Zhang +12
Large language models (LLMs) have achieved significant progress in solving complex reasoning tasks by Reinforcement Learning with Verifiable Rewards (RLVR). This advancement is als…
Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs
Yuzhe Gu, Wenwei Zhang, Chengqi Lyu +2
Large language models (LLMs) exhibit hallucinations (i.e., unfaithful or nonsensical information) when serving as AI assistants in various domains. Since hallucinations always come…
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning
Chengqi Lyu, Songyang Gao, Yuzhe Gu +14
Reasoning abilities, especially those for solving complex math problems, are crucial components of general intelligence. Recent advances by proprietary companies, such as o-series…