Key papers

• TREK: Distill to Explore, Reinforce to Refine (2026)
  Yuanda Xu et al.
  2.00
• Your Group-Relative Advantage Is Biased (2026)
  Fengkai Yang et al.
  1.94
• Length-Unbiased Sequence Policy Optimization: Revealing and Controlling Response Length Variation in RLVR (2026)
  Fanfan Liu et al.
  1.94
• Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration? (2026)
  Dadi Guo et al.
  1.94
• Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs? (2026)
  Jeonghye Kim et al.
  1.94
• Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3 (2026)
  Natapong Nitarach
  1.94
• Counting as a minimal probe of language model reliability (2026)
  Tianxiang Dai et al.
  1.94
• LEAD: Length-Efficient Adaptive and Dynamic Reasoning for Large Language Models (2026)
  Songtao Wei et al.
  1.94
• DenoiseRL: Bootstrapping Reasoning Models to Recover from Noisy Prefixes (2026)
  Caijun Xu et al.
  1.94
• Geometric Latent Reasoning Induces Shorter Generations in LLMs (2026)
  Shashi Kumar et al.
  1.94
• ComBench: A Benchmark for Rigorous Proof Reasoning and Constructive Realization in Olympiad-Level Combinatorics (2026)
  Shunkai Zhang et al.
  1.94
• N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization (2026)
  Xukun Zhu et al.
  1.94
• Teaching Language Models to Think in Code (2026)
  Hyeon Hwang et al.
  1.89
• Reasoning over mathematical objects: on-policy reward modeling and test time aggregation (2026)
  Pranjal Aggarwal et al.
  1.78
• Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation (2026)
  Zhuolin Yang et al.
  1.78
• An Ontology-Based Approach to Optimizing Geometry Problem Sets for Skill Development (2025)
  Michael Bouzinier et al.
  1.44
• Control LLM: Controlled Evolution for Intelligence Retention in LLM (2025)
  Haichao Wei et al.
  1.28
• Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models (2025)
  Sonam Gupta et al.
  1.28
• AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence (2025)
  Yuliang Liu et al.
  1.28
• VerifiAgent: a Unified Verification Agent in Language Model Reasoning (2025)
  Jiuzhou Han et al.
  1.28
• Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs (2025)
  Jaemin Kim et al.
  1.28
• Harnessing Negative Signals: Reinforcement Distillation from Teacher Data for LLM Reasoning (2025)
  Shuyao Xu et al.
  1.28
• CoRT: Code-integrated Reasoning within Thinking (2025)
  Chengpeng Li et al.
  1.28
• Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning (2025)
  Jikai Jin et al.
  1.28
• A Practical Two-Stage Recipe for Mathematical LLMs: Maximizing Accuracy with SFT and Efficiency with Reinforcement Learning (2025)
  Hiroshi Yoshihara et al.
  1.28
• AMFT: Aligning LLM Reasoners by Meta-Learning the Optimal Imitation-Exploration Balance (2025)
  Lixuan He et al.
  1.28
• Mol-R1: Towards Explicit Long-CoT Reasoning in Molecule Discovery (2025)
  Jiatong Li et al.
  1.28
• VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Use (2025)
  Dongfu Jiang et al.
  1.28
• Towards a Unified View of Large Language Model Post-Training (2025)
  Xingtai Lv et al.
  1.28
• VCRL: Variance-based Curriculum Reinforcement Learning for Large Language Models (2025)
  Guochao Jiang et al.
  1.28
• GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts (2025)
  Fan Yuan et al.
  1.28
• ExGRPO: Learning to Reason from Experience (2025)
  Runzhe Zhan et al.
  1.28
• Training-Free Group Relative Policy Optimization (2025)
  Yuzheng Cai et al.
  1.28
• CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images (2025)
  Chengqi Duan et al.
  1.28
• RAG-Anything: All-in-One RAG Framework (2025)
  Zirui Guo et al.
  1.28
• One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning (2023)
  Arnav Chavan et al.
  —
• ChatGPT for Robotics: Design Principles and Model Abilities (2023)
  Sai Vemprala et al.
  —
• Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023)
  Zheng Yuan et al.
  —
• MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code (2024)
  Zimu Lu et al.
  —
• DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models (2024)
  Chengke Zou et al.
  —
• B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners (2024)
  Weihao Zeng et al.
  —