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

468 papers, page 7 of 10

301. NeurIPS 2024Simplifying Constraint Inference with Inverse Reinforcement Learning
302. NeurIPS 2024Simplifying Latent Dynamics with Softly State-Invariant World Models
303. NeurIPS 2024Solving Minimum-Cost Reach Avoid using Reinforcement Learning
304. NeurIPS 2024Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
305. NeurIPS 2024Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
306. NeurIPS 2024SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning
307. NeurIPS 2024State Chrono Representation for Enhancing Generalization in Reinforcement Learning
308. NeurIPS 2024State-free Reinforcement Learning
309. NeurIPS 2024Statistical Efficiency of Distributional Temporal Difference Learning
310. NeurIPS 2024Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning
311. NeurIPS 2024Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning
312. NeurIPS 2024Swift Sampler: Efficient Learning of Sampler by 10 Parameters
313. NeurIPS 2024Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces
314. NeurIPS 2024The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning
315. NeurIPS 2024The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
316. NeurIPS 2024The Value of Reward Lookahead in Reinforcement Learning
317. NeurIPS 2024Time-Constrained Robust MDPs
318. NeurIPS 2024Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
319. NeurIPS 2024Unlock the Intermittent Control Ability of Model Free Reinforcement Learning
320. NeurIPS 2024Using Unity to Help Solve Reinforcement Learning
321. NeurIPS 2024Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
322. NeurIPS 2024XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
323. NeurIPS 2023A Definition of Continual Reinforcement Learning
324. NeurIPS 2023A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
325. NeurIPS 2023A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
326. NeurIPS 2023A State Representation for Diminishing Rewards
327. NeurIPS 2023Accelerating Exploration with Unlabeled Prior Data
328. NeurIPS 2023Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
329. NeurIPS 2023Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
330. NeurIPS 2023Accelerating Value Iteration with Anchoring
331. NeurIPS 2023Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
332. NeurIPS 2023Adversarial Model for Offline Reinforcement Learning
333. NeurIPS 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
334. NeurIPS 2023Anytime-Competitive Reinforcement Learning with Policy Prior
335. NeurIPS 2023Bayesian Risk-Averse Q-Learning with Streaming Observations
336. NeurIPS 2023Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback
337. NeurIPS 2023Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
338. NeurIPS 2023Bi-Level Offline Policy Optimization with Limited Exploration
339. NeurIPS 2023Budgeting Counterfactual for Offline RL
340. NeurIPS 2023CEIL: Generalized Contextual Imitation Learning
341. NeurIPS 2023Coherent Soft Imitation Learning
342. NeurIPS 2023Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
343. NeurIPS 2023Conservative State Value Estimation for Offline Reinforcement Learning
344. NeurIPS 2023Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning
345. NeurIPS 2023Context Shift Reduction for Offline Meta-Reinforcement Learning
346. NeurIPS 2023Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
347. NeurIPS 2023Corruption-Robust Offline Reinforcement Learning with General Function Approximation
348. NeurIPS 2023Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning
349. NeurIPS 2023CQM: Curriculum Reinforcement Learning with a Quantized World Model
350. NeurIPS 2023Creating Multi-Level Skill Hierarchies 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.