General ML · reinforcement learning papers, 2023–2026

Key findings

• General ML · reinforcement learning went from 287 papers in 2023 to 575 in 2026, roughly 2.0x in three years.
• ICLR publishes the most General ML · reinforcement learning work: 847 papers from 2023 to 2026, 51% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 2 in 2023 to 34 in 2026.
• Among the 6 topics under General Machine Learning, it ranks #2 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 2.0x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All General ML · reinforcement learning papers

1,676 papers, page 20 of 34

951. NeurIPS 2025REINFORCE Converges to Optimal Policies with Any Learning Rate
952. NeurIPS 2025Reinforcement Learning Finetunes Small Subnetworks in Large Language Models
953. NeurIPS 2025Reinforcement Learning with Backtracking Feedback
954. NeurIPS 2025Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach
955. NeurIPS 2025Reward-Aware Proto-Representations in Reinforcement Learning
956. NeurIPS 2025Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents
957. NeurIPS 2025Risk-Averse Total-Reward Reinforcement Learning
958. NeurIPS 2025RLVR-World: Training World Models with Reinforcement Learning
959. NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
960. NeurIPS 2025Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning
961. NeurIPS 2025SeRL: Self-play Reinforcement Learning for Large Language Models with Limited Data
962. NeurIPS 2025Shift Before You Learn: Enabling Low-Rank Representations in Reinforcement Learning
963. NeurIPS 2025ShiQ: Bringing back Bellman to LLMs
964. NeurIPS 2025Skill-Driven Neurosymbolic State Abstractions
965. NeurIPS 2025Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
966. NeurIPS 2025Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning
967. NeurIPS 2025Staggered Environment Resets Improve Massively Parallel On-Policy Reinforcement Learning
968. NeurIPS 2025STAIR: Addressing Stage Misalignment through Temporal-Aligned Preference Reinforcement Learning
969. NeurIPS 2025STAR: Efficient Preference-based Reinforcement Learning via Dual Regularization
970. NeurIPS 2025State Entropy Regularization for Robust Reinforcement Learning
971. NeurIPS 2025Structured Reinforcement Learning for Combinatorial Decision-Making
972. NeurIPS 2025Tackling Continual Offline RL through Selective Weights Activation on Aligned Spaces
973. NeurIPS 2025The World Is Bigger: A Computationally-Embedded Perspective on the Big World Hypothesis
974. NeurIPS 2025Time Reversal Symmetry for Efficient Robotic Manipulations in Deep Reinforcement Learning
975. NeurIPS 2025To Think or Not To Think: A Study of Thinking in Rule-Based Visual Reinforcement Fine-Tuning
976. NeurIPS 2025Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds
977. NeurIPS 2025Towards Provable Emergence of In-Context Reinforcement Learning
978. NeurIPS 2025Trajectory Graph Learning: Aligning with Long Trajectories in Reinforcement Learning Without Reward Design
979. NeurIPS 2025TTRL: Test-Time Reinforcement Learning
980. NeurIPS 2025Uncertainty-Sensitive Privileged Learning
981. NeurIPS 2025Unified Multimodal Chain-of-Thought Reward Model through Reinforcement Fine-Tuning
982. NeurIPS 2025Value Diffusion Reinforcement Learning
983. NeurIPS 2025Value Improved Actor Critic Algorithms
984. NeurIPS 2025Videos are Sample-Efficient Supervisions: Behavior Cloning from Videos via Latent Representations
985. NeurIPS 2025WHAT MAKES MATH PROBLEMS HARD FOR REINFORCEMENT LEARNING: A CASE STUDY
986. NeurIPS 2025When Can Model-Free Reinforcement Learning be Enough for Thinking?
987. CVPR 2024AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning
988. CVPR 2024Improving Unsupervised Hierarchical Representation with Reinforcement Learning
989. CVPR 2024Learning to Control Camera Exposure via Reinforcement Learning
990. CVPR 2024Regularized Parameter Uncertainty for Improving Generalization in Reinforcement Learning
991. ICLR 2024$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis
992. ICLR 2024A Dynamical View of the Question of Why
993. ICLR 2024Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
994. ICLR 2024Adaptive Rational Activations to Boost Deep Reinforcement Learning
995. ICLR 2024Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
996. ICLR 2024Addressing Signal Delay in Deep Reinforcement Learning
997. ICLR 2024Adversarial Imitation Learning via Boosting
998. ICLR 2024AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
999. ICLR 2024AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
1000. ICLR 2024Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning

FAQ

How many General ML · reinforcement learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,676 in total: 287 in 2023, 403 in 2024, 411 in 2025, 575 in 2026.

How many General ML · reinforcement learning papers are at NeurIPS 2026?

NeurIPS 2026 has 113 General ML · reinforcement learning papers, versus 108 the year before.

How many General ML · reinforcement learning papers are at ICLR 2026?

ICLR 2026 has 335 General ML · reinforcement learning papers, versus 230 the year before.

How many General ML · reinforcement learning papers are at ICML 2026?

ICML 2026 has 113 General ML · reinforcement learning papers, versus 71 the year before.

How many General ML · reinforcement learning papers are at CVPR 2026?

CVPR 2026 has 14 General ML · reinforcement learning papers, versus 2 the year before.

Which conference publishes the most General ML · reinforcement learning papers?

ICLR, with 847 papers from 2023 to 2026.