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 29 of 34

1401. ICLR 2023Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
1402. ICLR 2023CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
1403. ICLR 2023Confidence-Conditioned Value Functions for Offline Reinforcement Learning
1404. ICLR 2023Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
1405. ICLR 2023Decision Transformer under Random Frame Dropping
1406. ICLR 2023Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
1407. ICLR 2023Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
1408. ICLR 2023Distributional Meta-Gradient Reinforcement Learning
1409. ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
1410. ICLR 2023Extreme Q-Learning: MaxEnt RL without Entropy
1411. ICLR 2023Gray-Box Gaussian Processes for Automated Reinforcement Learning
1412. ICLR 2023Guiding Safe Exploration with Weakest Preconditions
1413. ICLR 2023Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
1414. ICLR 2023HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings
1415. ICLR 2023Human-level Atari 200x faster
1416. ICLR 2023Hyperbolic Deep Reinforcement Learning
1417. ICLR 2023Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
1418. ICLR 2023In-context Reinforcement Learning with Algorithm Distillation
1419. ICLR 2023In-sample Actor Critic for Offline Reinforcement Learning
1420. ICLR 2023Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function
1421. ICLR 2023Latent Variable Representation for Reinforcement Learning
1422. ICLR 2023Learning About Progress From Experts
1423. ICLR 2023Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
1424. ICLR 2023Learning Soft Constraints From Constrained Expert Demonstrations
1425. ICLR 2023LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
1426. ICLR 2023Minimum Description Length Control
1427. ICLR 2023MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations
1428. ICLR 2023Near-Optimal Adversarial Reinforcement Learning with Switching Costs
1429. ICLR 2023Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
1430. ICLR 2023Near-optimal Policy Identification in Active Reinforcement Learning
1431. ICLR 2023Neural Episodic Control with State Abstraction
1432. ICLR 2023Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
1433. ICLR 2023Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization
1434. ICLR 2023On the Robustness of Safe Reinforcement Learning under Observational Perturbations
1435. ICLR 2023Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
1436. ICLR 2023PAC Reinforcement Learning for Predictive State Representations
1437. ICLR 2023Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
1438. ICLR 2023Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning
1439. ICLR 2023POPGym: Benchmarking Partially Observable Reinforcement Learning
1440. ICLR 2023Provably Efficient Lifelong Reinforcement Learning with Linear Representation
1441. ICLR 2023Quality-Similar Diversity via Population Based Reinforcement Learning
1442. ICLR 2023Quasi-optimal Reinforcement Learning with Continuous Actions
1443. ICLR 2023Recursive Time Series Data Augmentation
1444. ICLR 2023Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
1445. ICLR 2023RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
1446. ICLR 2023ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs
1447. ICLR 2023Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
1448. ICLR 2023Spectral Decomposition Representation for Reinforcement Learning
1449. ICLR 2023TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
1450. ICLR 2023Temporal Disentanglement of Representations for Improved Generalisation in 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.