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 16 / 17 页

751. ICLR 2024Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
752. ICLR 2024TD-MPC2: Scalable, Robust World Models for Continuous Control
753. ICLR 2024Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
754. ICLR 2024The Curse of Diversity in Ensemble-Based Exploration
755. ICLR 2024The Effective Horizon Explains Deep RL Performance in Stochastic Environments
756. ICLR 2024The Generalization Gap in Offline Reinforcement Learning
757. ICLR 2024The Update-Equivalence Framework for Decision-Time Planning
758. ICLR 2024The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
759. ICLR 2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
760. ICLR 2024TorchRL: A data-driven decision-making library for PyTorch
761. ICLR 2024Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games
762. ICLR 2024Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
763. ICLR 2024Towards Offline Opponent Modeling with In-context Learning
764. ICLR 2024Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
765. ICLR 2024Towards Principled Representation Learning from Videos for Reinforcement Learning
766. ICLR 2024Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
767. ICLR 2024Tree Search-Based Policy Optimization under Stochastic Execution Delay
768. ICLR 2024True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning
769. ICLR 2024Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning
770. ICLR 2024Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
771. ICLR 2024Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
772. ICLR 2024Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
773. ICLR 2024Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization
774. ICLR 2024Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
775. ICLR 2024Unlocking the Power of Representations in Long-term Novelty-based Exploration
776. ICLR 2024Unveiling Options with Neural Network Decomposition
777. ICLR 2024Vanishing Gradients in Reinforcement Finetuning of Language Models
778. ICLR 2024Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits
779. ICLR 2024Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning
780. ICLR 2024When should we prefer Decision Transformers for Offline Reinforcement Learning?
781. ICLR 2024Whittle Index with Multiple Actions and State Constraint for Inventory Management
782. ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
783. ICLR 2023Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
784. ICLR 2023Backstepping Temporal Difference Learning
785. ICLR 2023BC-IRL: Learning Generalizable Reward Functions from Demonstrations
786. ICLR 2023Become a Proficient Player with Limited Data through Watching Pure Videos
787. ICLR 2023Behavior Prior Representation learning for Offline Reinforcement Learning
788. ICLR 2023Benchmarking Constraint Inference in Inverse Reinforcement Learning
789. ICLR 2023Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
790. ICLR 2023Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
791. ICLR 2023CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
792. ICLR 2023Confidence-Conditioned Value Functions for Offline Reinforcement Learning
793. ICLR 2023Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
794. ICLR 2023Decision Transformer under Random Frame Dropping
795. ICLR 2023Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
796. ICLR 2023Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
797. ICLR 2023Distributional Meta-Gradient Reinforcement Learning
798. ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
799. ICLR 2023Extreme Q-Learning: MaxEnt RL without Entropy
800. ICLR 2023Gray-Box Gaussian Processes for Automated Reinforcement Learning

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。