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

575 papers, page 9 of 12

401. ICML 2026Learning What to Generate: A Reinforcement Learning-based Closed-Loop Augmentation Framework for Person Re-identification
402. ICML 2026Learning-To-Measure: In-Context Active Feature Acquisition
403. ICML 2026LightningRL: Breaking the Accuracy–Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning
404. ICML 2026Mind the Budget: Accelerating Deep Reinforcement Learning using Constrained Early Exit Neural Networks
405. ICML 2026Mirror Descent Actor Critic via Bounded Advantage Learning
406. ICML 2026Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis
407. ICML 2026Multivariate Distributional Reinforcement Learning Using Sliced Divergences
408. ICML 2026Neuro-evolutionary Continual Reinforcement Learning
409. ICML 2026Noise-Guided Transport: Imitation Learning from Random Priors
410. ICML 2026Non-Uniform Noise-to-Signal Ratio in the REINFORCE Policy-Gradient Estimator
411. ICML 2026Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment
412. ICML 2026Offline Reinforcement Learning with Universal Horizon Models
413. ICML 2026On the Role of Computation in Reinforcement Learning
414. ICML 2026Online Robust Reinforcement Learning with General Function Approximation
415. ICML 2026PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
416. ICML 2026PAMD: Structured Adaptive Distances for Bisimulation Representations in Visual Reinforcement Learning
417. ICML 2026PAWS: Preference Learning with Advantage-Weighted Segments
418. ICML 2026Performative Policy Gradient: Optimality in Performative Reinforcement Learning
419. ICML 2026PretrainZero: Reinforcement Active Learning on Pretraining Data
420. ICML 2026Prioritized Model Experience Replay
421. ICML 2026PRM-PBE: Process Reward Model for Reinforcement Learning in Programming-by-Example
422. ICML 2026Q-SAM: Unlocking Sharpness-Aware Minimization for Generalization in Offline Reinforcement Learning
423. ICML 2026Quantum Robust Inner Minimization for Reinforcement Learning with Quadratic Speed-Up in Query Complexity
424. ICML 2026Rate or Fate? RLV$^{\varepsilon}$R: Reinforcement Learning with Verifiable Noisy Rewards
425. ICML 2026Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality
426. ICML 2026Reinforcement Learning via Self-Distillation
427. ICML 2026Reinforcement Learning with Action-Triggered Observations
428. ICML 2026Replay Failures as Successes: Sample-Efficient Reinforcement Learning for Instruction Following
429. ICML 2026Rethinking the Hardness of PbRL: A Provable General Regret Bound
430. ICML 2026Rethinking the Trust Region in LLM Reinforcement Learning
431. ICML 2026Return-Critic: Bridging Goal Discrepancy for Efficient Visual Reinforcement Learning
432. ICML 2026Reward-Preserving Counterfactual State Editing for Offline Reinforcement Learning
433. ICML 2026RiskZero: Plan More to Risk Less with a Learned Model
434. ICML 2026RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning
435. ICML 2026Robust Sequential Experimental Design for A/B Testing
436. ICML 2026Safe In-Context Reinforcement Learning
437. ICML 2026Safe Reinforcement Learning with Preference-based Constraint Inference
438. ICML 2026Safety Generalization Under Distribution Shift in Safe Reinforcement Learning: A Diabetes Testbed
439. ICML 2026Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance
440. ICML 2026Scalable Option Learning in High-Throughput Environments
441. ICML 2026SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
442. ICML 2026SPHERE: Mitigating the Loss of Spectral Plasticity in Mixture-of-Experts for Deep Reinforcement Learning
443. ICML 2026Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
444. ICML 2026StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning
445. ICML 2026SVL: Goal-Conditioned Reinforcement Learning as Survival Learning
446. ICML 2026SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents
447. ICML 2026Taming Aleatoric Impulse in Off-Policy Reinforcement Learning
448. ICML 2026Test-time Offline Reinforcement Learning on Goal-related Experience
449. ICML 2026The Cost of Commitment in Option-Based Hierarchical RL
450. ICML 2026The Role of Target Update Frequencies in Q-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.