1 citations · 2 across the 9 of their papers we have counts for
11 papers
TPPO: Tracking-Value PPO For Language Model Reasoning
Futing Wang, Chenxi Li, Jianhao Yan +6
Proximal Policy Optimization (PPO) is widely used in reinforcement learning with verifiable rewards for language-model reasoning. While \emph{value evolution along trajectory} char…
Gains and Collapse in On-Policy Distillation:A Reinforcement Learning Perspective
Han Cui, Jianhao Yan, Yun Luo +3
On-policy distillation (OPD) has become an important approach to language model post-training. However, despite its performance gains, OPD can also collapse into excessively long a…
DeepInstructor: An Agentic AI Instructor for Experience-Driven Idea Evaluation
Rongcan Pei, Fang Guo, Qinglin Qi +7
As automated scientific discovery advances, Large Language Models (LLMs) can now generate research ideas at an unprecedented scale, shifting the bottleneck from idea generation to…
Detecting RLVR Training Data via Structural Convergence of Reasoning
Hongbo Zhang, Yue Yang, Jianhao Yan +2
Reinforcement learning with verifiable rewards (RLVR) is central to training modern reasoning models, but the undisclosed training data raises concerns about benchmark contaminatio…
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…
P1-VL: Bridging Visual Perception and Scientific Reasoning in Physics Olympiads
Yun Luo, Futing Wang, Qianjia Cheng +28
The transition from symbolic manipulation to science-grade reasoning represents a pivotal frontier for Large Language Models (LLMs), with physics serving as the critical test ancho…
BAPO: Boundary-Aware Policy Optimization for Reliable Agentic Search
Shiyu Liu, Yongjing Yin, Jianhao Yan +7
RL-based agentic search enables LLMs to solve complex questions via dynamic planning and external search. While this approach significantly enhances accuracy with agent policies op…
External Hippocampus: Topological Cognitive Maps for Guiding Large Language Model Reasoning
Jian Yan
This paper proposes the External Hippocampus framework, which models language model reasoning from a cognitive dynamics perspective as the flow of information energy in semantic sp…
Diversity-Incentivized Exploration for Versatile Reasoning
Zican Hu, Shilin Zhang, Yafu Li +7
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a crucial paradigm for incentivizing reasoning capabilities in Large Language Models (LLMs). Due to vast state-…
Unveiling Attractor Cycles in Large Language Models: A Dynamical Systems View of Successive Paraphrasing
Zhilin Wang, Yafu Li, Jianhao Yan +2
Dynamical systems theory provides a framework for analyzing iterative processes and evolution over time. Within such systems, repetitive transformations can lead to stable configur…
Dynamics of Instruction Fine-Tuning for Chinese Large Language Models
Chiyu Song, Zhanchao Zhou, Jianhao Yan +3
Instruction tuning is a burgeoning method to elicit the general intelligence of Large Language Models (LLMs). While numerous studies have examined the impact of factors such as dat…