通用机器学习 · reinforcement learning论文趋势 2023–2026

主要结论

• 通用机器学习 · reinforcement learning论文从 2023 年的 287 篇增长到 2026 年的 575 篇，三年间扩大到约 2.0 倍。
• ICLR 是发通用机器学习 · reinforcement learning论文最多的会议，2023–2026 年共 847 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 34 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 2；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · reinforcement learning是 2.0 倍。

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

• NeurIPS 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
• ICML 2026De-attribute to Forget for LLM Unlearning
• ICLR 2026AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
• CVPR 2026Dynamic Important Example Mining for Reinforcement Finetuning
• NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
• ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
• ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
• CVPR 2025Automated Proof of Polynomial Inequalities via Reinforcement Learning
• NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
• ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
• ICLR 2024Bandits with Replenishable Knapsacks: the Best of both Worlds
• CVPR 2024Improving Unsupervised Hierarchical Representation with Reinforcement Learning
• NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
• ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
• ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
• CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
• NeurIPS 2026Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
• ICML 2026Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
• ICLR 2026APPLE: Toward General Active Perception via Reinforcement Learning
• CVPR 2026Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

全部通用机器学习 · reinforcement learning论文

共 1,676 篇，第 10 / 34 页

451. ICML 2026The Surprising Difficulty of Search in Model-Based Reinforcement Learning
452. ICML 2026TQL: Scaling Q-Functions with Transformers by Preventing Attention Collapse
453. ICML 2026TraCeS: Learning Per-Timestep Constraint-Violation Credit from Sparse Trajectory-Level Labels
454. ICML 2026Trajectory-Level Data Augmentation for Offline Reinforcement Learning
455. ICML 2026Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
456. ICML 2026Trust Region Masking for Long-Horizon LLM Reinforcement Learning
457. ICML 2026TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
458. ICML 2026Video-Based Optimal Transport for Feedback-Efficient Offline Preference-Based Reinforcement Learning
459. ICML 2026VideoSEG-O3: A Multi-turn Reinforcement Learning Framework for Reasoning Video Object Segmentation
460. ICML 2026VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
461. ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
462. ICML 2026Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
463. NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
464. NeurIPS 2026$f$-GRPO & Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment
465. NeurIPS 2026A Geometric Perspective on Reward Function Updates in Inverse Reinforcement Learning
466. NeurIPS 2026A New Framework for Quantum Reinforcement Learning
467. NeurIPS 2026A Primal-dual Approach for Semi-Infinitely Constrained Reinforcement Learning
468. NeurIPS 2026Accelerating Safe Reinforcement Learning with Massive Parallelism
469. NeurIPS 2026ACQueReLlo: Alignment-Aware Constrained Quantization via Reinforcement Learning for Large Language Models
470. NeurIPS 2026Adaptive Stepsizes for Eligibility Traces in Deep Reinforcement Learning
471. NeurIPS 2026Addressing Sparse-Rewards in RL with Scalable Hierarchical Novel Eigen Options
472. NeurIPS 2026AGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games
473. NeurIPS 2026AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs
474. NeurIPS 2026Behavior-Discriminative Reward Shaping for Reward-Robust Reinforcement Learning
475. NeurIPS 2026Benign Reinforcement Learning Can Amplify Latent Backdoors
476. NeurIPS 2026Conservatism Controllable Compositional Guidance for Offline Safe Reinforcement Learning
477. NeurIPS 2026Context Value Informed In-Context Reinforcement Learning
478. NeurIPS 2026Cross-Question Reliable Reinforcement Learning
479. NeurIPS 2026CS-DICE: Offline Reinforcement Learning with Coherent Occupancy Regularization
480. NeurIPS 2026CURe: Conservative Unlearning with Soft-Gating Regularization for Offline Reinforcement Learning
481. NeurIPS 2026DACA-GRPO: Denoising-Aware Credit Assignment for Reinforcement Learning in Diffusion Language Models
482. NeurIPS 2026DARLING: Detection Augmented Reinforcement Learning with Non-Stationary Guarantees
483. NeurIPS 2026Deep Double Q-learning
484. NeurIPS 2026Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View
485. NeurIPS 2026DGRAF: Observation-Quality-Aware Reinforcement Learning for Dynamic Reconfigurable Batteries
486. NeurIPS 2026Diffusion Subgoal Planning for Long-Horizon Offline Goal-Conditioned Reinforcement Learning
487. NeurIPS 2026DiReCL: Learning Differentiable Reward Code with Inverse Reinforcement Learning
488. NeurIPS 2026Distribution Corrected Decision Transformer for Offline Reinforcement Learning with Imbalanced Datasets
489. NeurIPS 2026DiversePlace: Diversity-Seeking Curriculum Reinforcement Learning for Macro Placement
490. NeurIPS 2026DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training
491. NeurIPS 2026Drift Q-Learning
492. NeurIPS 2026DUDS: Dual-stage Data Selection for Efficient Reinforcement Learning with Verifiable Rewards
493. NeurIPS 2026Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty
494. NeurIPS 2026DynamAuction: a reinforcement learning environment for repeated auction with dynamic value
495. NeurIPS 2026ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning
496. NeurIPS 2026Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
497. NeurIPS 2026Escaping Path Mirages in Offline Goal-Conditioned Reinforcement Learning
498. NeurIPS 2026EventLens: Event-Structure Reinforcement Learning for Video Understanding
499. NeurIPS 2026Evolutionary System Prompt Learning for Reinforcement Learning in LLMs
500. NeurIPS 2026Flow Matching Reinforcement Learning via SDE Inference

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · reinforcement learning论文？

共 1,676 篇，按年份分别是 2023 年 287 篇、2024 年 403 篇、2025 年 411 篇、2026 年 575 篇。

NeurIPS 2026 有多少篇通用机器学习 · reinforcement learning论文？

NeurIPS 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 108 篇。

ICLR 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICLR 2026 有 335 篇通用机器学习 · reinforcement learning论文，上一届是 230 篇。

ICML 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICML 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 71 篇。

CVPR 2026 有多少篇通用机器学习 · reinforcement learning论文？

CVPR 2026 有 14 篇通用机器学习 · reinforcement learning论文，上一届是 2 篇。

哪个会议的通用机器学习 · reinforcement learning论文最多？

ICLR，2023–2026 年共 847 篇。