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

847 papers, page 7 of 17

301. ICLR 2026Text2Grad: Reinforcement Learning from Natural Language Feedback
302. ICLR 2026The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward
303. ICLR 2026The Rank and Gradient Lost in Non-stationarity: Sample Weight Decay for Mitigating Plasticity Loss in Reinforcement Learning
304. ICLR 2026The State of Reinforcement Finetuning for Transformer-based Generative Agents
305. ICLR 2026TimeSearch-R: Adaptive Temporal Search for Long-Form Video Understanding via Self-Verification Reinforcement Learning
306. ICLR 2026TIPS: Turn-level Information-Potential Reward Shaping for Search-Augmented LLMs
307. ICLR 2026Toward Conservative Planning from Preferences in Offline Reinforcement Learning
308. ICLR 2026Toward Efficient Exploration by Large Language Model Agents
309. ICLR 2026Towards Bridging the Gap between Large-Scale Pretraining and Efficient Finetuning for Humanoid Control
310. ICLR 2026Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
311. ICLR 2026Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward
312. ICLR 2026TRACED: Transition-aware Regret Approximation with Co-learnability for Environment Design
313. ICLR 2026Trajectory Generation with Conservative Value Guidance for Offline Reinforcement Learning
314. ICLR 2026Transitive RL: Value Learning via Divide and Conquer
315. ICLR 2026Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?
316. ICLR 2026TROLL: Trust Regions Improve Reinforcement Learning for Large Language Models
317. ICLR 2026Trust-Region Adaptive Policy Optimization
318. ICLR 2026Uncovering Robot Vulnerabilities through Semantic Potential Fields
319. ICLR 2026Understanding and Improving Hyperbolic Deep Reinforcement Learning
320. ICLR 2026Universal Value-Function Uncertainties
321. ICLR 2026Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
322. ICLR 2026Unsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals
323. ICLR 2026Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning
324. ICLR 2026Value Flows
325. ICLR 2026Value Gradient Flow: Behavior-Regularized RL without Regularization
326. ICLR 2026Variance-Dependent Regret Lower Bounds for Contextual Bandits
327. ICLR 2026VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool Use
328. ICLR 2026Wavelet Predictive Representations for Non-Stationary Reinforcement Learning
329. ICLR 2026WebArbiter: A Generative Reasoning Process Reward Model for Web Agents
330. ICLR 2026What Matters for Batch Online Reinforcement Learning in Robotics?
331. ICLR 2026Who Matters Matters: Agent-Specific Conservative Offline MARL
332. ICLR 2026WIMLE: Uncertainty‑Aware World Models with IMLE for Sample‑Efficient Continuous Control
333. ICLR 2026WorldGym: World Model as An Environment for Policy Evaluation
334. ICLR 2026XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning
335. ICLR 2026Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics
336. ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
337. ICLR 2025$q$-exponential family for policy optimization
338. ICLR 2025A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations
339. ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
340. ICLR 2025A Generalist Hanabi Agent
341. ICLR 2025A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
342. ICLR 2025A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals
343. ICLR 2025A Theoretical Framework for Partially-Observed Reward States in RLHF
344. ICLR 2025Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research
345. ICLR 2025Accelerating Task Generalisation with Multi-Level Skill Hierarchies
346. ICLR 2025ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample $V$-Ensemble
347. ICLR 2025ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
348. ICLR 2025Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
349. ICLR 2025Advantage Alignment Algorithms
350. ICLR 2025Adversarial Policy Optimization for Offline Preference-based 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.