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 847 篇，第 12 / 17 页

551. ICLR 2025Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction
552. ICLR 2025Trajectory-Class-Aware Multi-Agent Reinforcement Learning
553. ICLR 2025Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning
554. ICLR 2025Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback
555. ICLR 2025Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
556. ICLR 2025UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP
557. ICLR 2025Utilitarian Algorithm Configuration for Infinite Parameter Spaces
558. ICLR 2025UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning
559. ICLR 2025Value-aligned Behavior Cloning for Offline Reinforcement Learning via Bi-level Optimization
560. ICLR 2025Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
561. ICLR 2025VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation
562. ICLR 2025What Makes a Good Diffusion Planner for Decision Making?
563. ICLR 2025XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
564. ICLR 2025Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models
565. ICLR 2025Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
566. ICLR 2024$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis
567. ICLR 2024A Dynamical View of the Question of Why
568. ICLR 2024Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
569. ICLR 2024Adaptive Rational Activations to Boost Deep Reinforcement Learning
570. ICLR 2024Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
571. ICLR 2024Addressing Signal Delay in Deep Reinforcement Learning
572. ICLR 2024Adversarial Imitation Learning via Boosting
573. ICLR 2024AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
574. ICLR 2024AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
575. ICLR 2024Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning
576. ICLR 2024Augmented Bayesian Policy Search
577. ICLR 2024Bandits with Replenishable Knapsacks: the Best of both Worlds
578. ICLR 2024Behaviour Distillation
579. ICLR 2024Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
580. ICLR 2024Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods
581. ICLR 2024Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies
582. ICLR 2024Blending Imitation and Reinforcement Learning for Robust Policy Improvement
583. ICLR 2024Bridging State and History Representations: Understanding Self-Predictive RL
584. ICLR 2024Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game
585. ICLR 2024Cascading Reinforcement Learning
586. ICLR 2024CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
587. ICLR 2024Chain of Hindsight aligns Language Models with Feedback
588. ICLR 2024Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
589. ICLR 2024Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
590. ICLR 2024Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
591. ICLR 2024Confronting Reward Model Overoptimization with Constrained RLHF
592. ICLR 2024Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
593. ICLR 2024Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning
594. ICLR 2024Contrastive Difference Predictive Coding
595. ICLR 2024Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning
596. ICLR 2024COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL
597. ICLR 2024CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
598. ICLR 2024Curiosity-driven Red-teaming for Large Language Models
599. ICLR 2024Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
600. ICLR 2024Decoupling regularization from the action space

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。