强化学习论文趋势 2023–2026

策略优化、离线 RL 与基于环境的决策学习

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 6,885 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

强化学习论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023484233297561,070
2024466304356641,190
2025784379405721,640
20267609111,0212932,985

代表论文

按年份和会议均匀挑选,方便快速看到每一届的样貌

全部强化学习论文

共 2,494 篇,第 29 / 50 页

  1. NeurIPS 2025Spatial-Aware Decision-Making with Ring Attractors in Reinforcement Learning Systems
  2. NeurIPS 2025SPC: Evolving Self-Play Critic via Adversarial Games for LLM Reasoning
  3. NeurIPS 2025Spectral Learning for Infinite-Horizon Average-Reward POMDPs
  4. NeurIPS 2025SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer
  5. NeurIPS 2025SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
  6. NeurIPS 2025SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
  7. NeurIPS 2025SRPO: Enhancing Multimodal LLM Reasoning via Reflection-Aware Reinforcement Learning
  8. NeurIPS 2025Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning
  9. NeurIPS 2025Staggered Environment Resets Improve Massively Parallel On-Policy Reinforcement Learning
  10. NeurIPS 2025STAIR: Addressing Stage Misalignment through Temporal-Aligned Preference Reinforcement Learning
  11. NeurIPS 2025STAR: Efficient Preference-based Reinforcement Learning via Dual Regularization
  12. NeurIPS 2025State Entropy Regularization for Robust Reinforcement Learning
  13. NeurIPS 2025State-Covering Trajectory Stitching for Diffusion Planners
  14. NeurIPS 2025Steering Generative Models with Experimental Data for Protein Fitness Optimization
  15. NeurIPS 2025STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation
  16. NeurIPS 2025Stochastic Principal-Agent Problems: Computing and Learning Optimal History-Dependent Policies
  17. NeurIPS 2025Stop Summation: Min-Form Credit Assignment Is All Process Reward Model Needs for Reasoning
  18. NeurIPS 2025Strategyproof Reinforcement Learning from Human Feedback
  19. NeurIPS 2025Structural Information-based Hierarchical Diffusion for Offline Reinforcement Learning
  20. NeurIPS 2025Structure Matters: Dynamic Policy Gradient
  21. NeurIPS 2025Structured Reinforcement Learning for Combinatorial Decision-Making
  22. NeurIPS 2025Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control
  23. NeurIPS 2025SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models
  24. NeurIPS 2025SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents
  25. NeurIPS 2025SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
  26. NeurIPS 2025SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning
  27. NeurIPS 2025SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
  28. NeurIPS 2025Systematic Reward Gap Optimization for Mitigating VLM Hallucinations
  29. NeurIPS 2025T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT
  30. NeurIPS 2025Table2LaTeX-RL: High-Fidelity LaTeX Code Generation from Table Images via Reinforced Multimodal Language Models
  31. NeurIPS 2025Tackling Continual Offline RL through Selective Weights Activation on Aligned Spaces
  32. NeurIPS 2025Tapered Off-Policy REINFORCE - Stable and efficient reinforcement learning for large language models
  33. NeurIPS 2025Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignment
  34. NeurIPS 2025Teaching Language Models to Reason with Tools
  35. NeurIPS 2025Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving
  36. NeurIPS 2025Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following
  37. NeurIPS 2025Temporal-Difference Variational Continual Learning
  38. NeurIPS 2025TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning for Video LLMs
  39. NeurIPS 2025TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture search
  40. NeurIPS 2025Test-Time Scaling of Diffusion Models via Noise Trajectory Search
  41. NeurIPS 2025Text-to-Decision Agent: Offline Meta-Reinforcement Learning from Natural Language Supervision
  42. NeurIPS 2025The Overthinker's DIET: Cutting Token Calories with DIfficulty-AwarE Training
  43. NeurIPS 2025The Promise of RL for Autoregressive Image Editing
  44. NeurIPS 2025The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning
  45. NeurIPS 2025The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
  46. NeurIPS 2025The World Is Bigger: A Computationally-Embedded Perspective on the Big World Hypothesis
  47. NeurIPS 2025Think before Recommendation: Autonomous Reasoning-enhanced Recommender
  48. NeurIPS 2025Think Only When You Need with Large Hybrid-Reasoning Models
  49. NeurIPS 2025Think or Not? Selective Reasoning via Reinforcement Learning for Vision-Language Models
  50. NeurIPS 2025Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查强化学习在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "reinforcement-learning"}

两分钟接入 Paperlist MCP(Claude Code、Cursor、Codex、ChatGPT)

常见问题

2023–2026 年四大会议一共有多少篇强化学习论文?
共 6,885 篇,按年份分别是 2023 年 1,070 篇、2024 年 1,190 篇、2025 年 1,640 篇、2026 年 2,985 篇。
NeurIPS 2026 有多少篇强化学习论文?
NeurIPS 2026 有 760 篇强化学习论文,上一届是 784 篇。
ICLR 2026 有多少篇强化学习论文?
ICLR 2026 有 911 篇强化学习论文,上一届是 379 篇。
ICML 2026 有多少篇强化学习论文?
ICML 2026 有 1,021 篇强化学习论文,上一届是 405 篇。
CVPR 2026 有多少篇强化学习论文?
CVPR 2026 有 293 篇强化学习论文,上一届是 72 篇。
哪个会议的强化学习论文最多?
NeurIPS,2023–2026 年共 2,494 篇。