Reinforcement Learning papers, 2023–2026

Key findings

• Reinforcement Learning went from 1,070 papers in 2023 to 2,985 in 2026, roughly 2.8x in three years.
• NeurIPS publishes the most Reinforcement Learning work: 2,494 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Reasoning Models: papers tagged with both rose from 9 in 2023 to 437 in 2026.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
• ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
• ICLR 2026$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space
• CVPR 2026A Causal Marriage between VLM and IRM from Understanding to
• NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
• ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
• ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
• CVPR 2025All-Optical Nonlinear Diffractive Deep Network for Ultrafast Image Denoising
• NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
• ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
• ICLR 2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
• CVPR 2024DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning
• NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
• ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
• ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
• CVPR 2023"Seeing" Electric Network Frequency From Events
• NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
• ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
• ICLR 2026$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning
• CVPR 2026AdaptVision Efficient Vision-Language Models via Adaptive Visual Acquisition

All Reinforcement Learning papers

760 papers, page 10 of 16

451. NeurIPS 2026Online Decision-Focused Learning under Semi-Bandit Feedback
452. NeurIPS 2026OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents
453. NeurIPS 2026OpenSearcher: Democratizing Deep Search through a Fully Offline Pipeline with Programmatic Verification
454. NeurIPS 2026OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents
455. NeurIPS 2026Optimistic Q-value Adaptation for Offline-to-Online Reinforcement Learning
456. NeurIPS 2026Optimizer-Induced Mode Connectivity: From AdamW to Muon
457. NeurIPS 2026Optimizing Agent Tool-Use via Trajectory-based Insight Evolution
458. NeurIPS 2026Optimizing Social Utility in Sequential Experiments
459. NeurIPS 2026Ordered Policy Optimization
460. NeurIPS 2026Outbidding and Outbluffing Elite Humans: Mastering Liar’s Poker via Self-Play and Reinforcement Learning
461. NeurIPS 2026Outcome-Based RL Provably Leads Transformers to Reason, but Only With the Right Data
462. NeurIPS 2026Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning
463. NeurIPS 2026PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents
464. NeurIPS 2026PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control
465. NeurIPS 2026Parallel Computation Algorithms and Convergence Guarantees for Mean-Field Langevin Dynamics
466. NeurIPS 2026Parameter Exploration for RLVR via Variational Learning
467. NeurIPS 2026ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning
468. NeurIPS 2026PASSAGE: A Real-Terrain Benchmark for Trustworthy Constrained Path Planning
469. NeurIPS 2026PatternBloom: Empowering Agentic RAG with Externalized RL-Distilled Graph Patterns
470. NeurIPS 2026Perception Without Engagement: Dissecting the Causal Discovery Deficit in LMMs
471. NeurIPS 2026Personalized and Collaborative Online LQR via Thompson Sampling
472. NeurIPS 2026Persuasive Prediction via Decision Calibration
473. NeurIPS 2026Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning
474. NeurIPS 2026PhGPO: Pheromone-Guided Policy Optimization for Long-Horizon Tool Planning
475. NeurIPS 2026PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation
476. NeurIPS 2026PhysTacGen: Physics-Aware Visual-Tactile Sensor Image Generation
477. NeurIPS 2026PiCA: Pivot-Based Credit Assignment For Search Agentic Reinforcement Learning
478. NeurIPS 2026Plan2Sense: Open-World Task Planning in Epistemic States via Interleaved Ontic and Sensing Actions
479. NeurIPS 2026PLATO: Pointer Learner for Agent and Task Openness
480. NeurIPS 2026Plausible Biomolecular Structure Prediction via Physics-informed Reinforcement Learning
481. NeurIPS 2026PO-PDDL: Learning Symbolic POMDPs from Visual Demonstrations for Robot Planning Under Uncertainty
482. NeurIPS 2026PoEM: Predicting New RL Outcomes from Existing Policies
483. NeurIPS 2026Policy Gradient Algorithms in Average-Reward Multichain MDPs
484. NeurIPS 2026Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering
485. NeurIPS 2026Policy-Level Exploration for Coordinated Multi-Agent Reinforcement Learning
486. NeurIPS 2026Posterior Sampling-based Online Learning for Episodic POMDPs
487. NeurIPS 2026Power Distribution Bridges Sampling, Self-Reward RL, and Self-Distillation
488. NeurIPS 2026PRECISE: SDE-Consistent Stochastic Sampling for RL Post-Training of Flow-Matching Models
489. NeurIPS 2026Preference Conditioned Multi-Objective Reinforcement Learning: Decomposed, Diversity-Driven Policy Optimization
490. NeurIPS 2026PreFT: Prefill-only finetuning for inference efficiency
491. NeurIPS 2026Preserving Exploration for LLM Reasoning via Mean Order-Statistic Alignment
492. NeurIPS 2026Prevailing Bisimulation Metric Learning Is Biased: Implicit Regularization and Its Remedy
493. NeurIPS 2026PriFT: Prior-Support Guided Token Reweighting for Supervised Fine-Tuning
494. NeurIPS 2026Principled Policy Optimization for LLMs via Self-Normalized Importance Sampling
495. NeurIPS 2026ProgramBench: Can Language Models Rebuild Programs From Scratch?
496. NeurIPS 2026Programmatic Reasoning with Structural Schema: A Unified Framework for Multi-Table Inference
497. NeurIPS 2026Proportionality in Ranking Compression
498. NeurIPS 2026Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction–Reality Gaps
499. NeurIPS 2026Provably Safe, Yet Performant Reinforcement Learning
500. NeurIPS 2026Pushing Biomolecular Utility-Diversity Frontiers with Supergroup Relative Policy Optimization

FAQ

How many Reinforcement Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

6,885 in total: 1,070 in 2023, 1,190 in 2024, 1,640 in 2025, 2,985 in 2026.

How many Reinforcement Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 760 Reinforcement Learning papers, versus 784 the year before.

How many Reinforcement Learning papers are at ICLR 2026?

ICLR 2026 has 911 Reinforcement Learning papers, versus 379 the year before.

How many Reinforcement Learning papers are at ICML 2026?

ICML 2026 has 1,021 Reinforcement Learning papers, versus 405 the year before.

How many Reinforcement Learning papers are at CVPR 2026?

CVPR 2026 has 293 Reinforcement Learning papers, versus 72 the year before.

Which conference publishes the most Reinforcement Learning papers?

NeurIPS, with 2,494 papers from 2023 to 2026.