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 19 of 34

901. NeurIPS 2025Computational Hardness of Reinforcement Learning with Partial $q^{\pi}$-Realizability
902. NeurIPS 2025DAIL: Beyond Task Ambiguity for Language-Conditioned Reinforcement Learning
903. NeurIPS 2025DAPO: An Open-Source LLM Reinforcement Learning System at Scale
904. NeurIPS 2025DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning
905. NeurIPS 2025Doubly Robust Alignment for Large Language Models
906. NeurIPS 2025Dynamic Configuration for Cutting Plane Separators via Reinforcement Learning on Incremental Graph
907. NeurIPS 2025Efficient Preference-Based Reinforcement Learning: Randomized Exploration meets Experimental Design
908. NeurIPS 2025Eluder dimension: localise it!
909. NeurIPS 2025Enhancing Interpretability in Deep Reinforcement Learning through Semantic Clustering
910. NeurIPS 2025Explainably Safe Reinforcement Learning
911. NeurIPS 2025FANS: A Flatness-Aware Network Structure for Generalization in Offline Reinforcement Learning
912. NeurIPS 2025Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features
913. NeurIPS 2025From Experts to a Generalist: Toward General Whole-Body Control for Humanoid Robots
914. NeurIPS 2025Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty
915. NeurIPS 2025General-Reasoner: Advancing LLM Reasoning Across All Domains
916. NeurIPS 2025Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithm
917. NeurIPS 2025Greedy Sampling Is Provably Efficient For RLHF
918. NeurIPS 2025Gymnasium: A Standard Interface for Reinforcement Learning Environments
919. NeurIPS 2025Horizon Reduction Makes RL Scalable
920. NeurIPS 2025How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning
921. NeurIPS 2025Imagined Autocurricula
922. NeurIPS 2025Imitation Beyond Expectation Using Pluralistic Stochastic Dominance
923. NeurIPS 2025Imitation Learning with Temporal Logic Constraints
924. NeurIPS 2025Improving Model-Based Reinforcement Learning by Converging to Flatter Minima
925. NeurIPS 2025Improving Reward Models with Proximal Policy Exploration for Preference-Based Reinforcement Learning
926. NeurIPS 2025Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning
927. NeurIPS 2025Learning Parameterized Skills from Demonstrations
928. NeurIPS 2025Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewards
929. NeurIPS 2025Learning to Clean: Reinforcement Learning for Noisy Label Correction
930. NeurIPS 2025Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning
931. NeurIPS 2025Meta-learning how to Share Credit among Macro-Actions
932. NeurIPS 2025Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning
933. NeurIPS 2025Mixture-of-Experts Meets In-Context Reinforcement Learning
934. NeurIPS 2025Novel Exploration via Orthogonality
935. NeurIPS 2025Offline Actor-Critic for Average Reward MDPs
936. NeurIPS 2025Offline Goal-conditioned Reinforcement Learning with Quasimetric Representations
937. NeurIPS 2025Offline imitation learning in $Q^\pi$-realizable MDPs without expert realizability
938. NeurIPS 2025Omni-R1: Reinforcement Learning for Omnimodal Reasoning via Two-System Collaboration
939. NeurIPS 2025On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
940. NeurIPS 2025On the Sample Complexity Bounds of Bilevel Reinforcement Learning
941. NeurIPS 2025Optimal Dynamic Regret by Transformers for Non-Stationary Reinforcement Learning
942. NeurIPS 2025Optimal Regret Bounds via Low-Rank Structured Variation in Non-Stationary Reinforcement Learning
943. NeurIPS 2025Option-aware Temporally Abstracted Value for Offline Goal-Conditioned Reinforcement Learning
944. NeurIPS 2025Perception-R1: Pioneering Perception Policy with Reinforcement Learning
945. NeurIPS 2025Preference Distillation via Value based Reinforcement Learning
946. NeurIPS 2025Preference-based Reinforcement Learning beyond Pairwise Comparisons: Benefits of Multiple Options
947. NeurIPS 2025Pretraining a Shared Q-Network for Data-Efficient Offline Reinforcement Learning
948. NeurIPS 2025Progress Reward Model for Reinforcement Learning via Large Language Models
949. NeurIPS 2025Quantization-Free Autoregressive Action Transformer
950. NeurIPS 2025Real-World Reinforcement Learning of Active Perception Behaviors

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.