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

784 papers, page 10 of 16

451. NeurIPS 2025Oryx: a Scalable Sequence Model for Many-Agent Coordination in Offline MARL
452. NeurIPS 2025OSVI-WM: One-Shot Visual Imitation for Unseen Tasks using World-Model-Guided Trajectory Generation
453. NeurIPS 2025Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
454. NeurIPS 2025OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
455. NeurIPS 2025Pairwise Calibrated Rewards for Pluralistic Alignment
456. NeurIPS 2025Parameter Efficient Fine-tuning via Explained Variance Adaptation
457. NeurIPS 2025PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimization
458. NeurIPS 2025Partner Modelling Emerges in Recurrent Agents (But Only When It Matters)
459. NeurIPS 2025Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
460. NeurIPS 2025Perception-R1: Pioneering Perception Policy with Reinforcement Learning
461. NeurIPS 2025Periodic Skill Discovery
462. NeurIPS 2025PeRL: Permutation-Enhanced Reinforcement Learning for Interleaved Vision-Language Reasoning
463. NeurIPS 2025Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing
464. NeurIPS 2025Physics-informed Value Learner for Offline Goal-Conditioned Reinforcement Learning
465. NeurIPS 2025PhysVLM-AVR: Active Visual Reasoning for Multimodal Large Language Models in Physical Environments
466. NeurIPS 2025Pixel Reasoner: Incentivizing Pixel Space Reasoning via Curiosity-Driven Reinforcement Learning
467. NeurIPS 2025Planning and Learning in Average Risk-aware MDPs
468. NeurIPS 2025Planning with Quantized Opponent Models
469. NeurIPS 2025Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL
470. NeurIPS 2025Plasticity as the Mirror of Empowerment
471. NeurIPS 2025Point-RFT: Improving Multimodal Reasoning with Visually Grounded Reinforcement Finetuning
472. NeurIPS 2025PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
473. NeurIPS 2025Policy Compatible Skill Incremental Learning via Lazy Learning Interface
474. NeurIPS 2025Policy Gradient Methods Converge Globally in Imperfect-Information Extensive-Form Games
475. NeurIPS 2025Policy Optimized Text-to-Image Pipeline Design
476. NeurIPS 2025Praxis-VLM: Vision-Grounded Decision Making via Text-Driven Reinforcement Learning
477. NeurIPS 2025Pre-Trained Policy Discriminators are General Reward Models
478. NeurIPS 2025Predictive Coding Enhances Meta-RL To Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
479. NeurIPS 2025Predictive Preference Learning from Human Interventions
480. NeurIPS 2025Preference Distillation via Value based Reinforcement Learning
481. NeurIPS 2025Preference Optimization on Pareto Sets: On a Theory of Multi-Objective Optimization
482. NeurIPS 2025Preference-based Reinforcement Learning beyond Pairwise Comparisons: Benefits of Multiple Options
483. NeurIPS 2025Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
484. NeurIPS 2025Preserving LLM Capabilities through Calibration Data Curation: From Analysis to Optimization
485. NeurIPS 2025Pretraining a Shared Q-Network for Data-Efficient Offline Reinforcement Learning
486. NeurIPS 2025PRIMT: Preference-based Reinforcement Learning with Multimodal Feedback and Trajectory Synthesis from Foundation Models
487. NeurIPS 2025Principled Fine-tuning of LLMs from User-Edits: A Medley of Preference, Supervision, and Reward
488. NeurIPS 2025PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs
489. NeurIPS 2025Prior-Guided Diffusion Planning for Offline Reinforcement Learning
490. NeurIPS 2025Probing Hidden Knowledge Holes in Unlearned LLMs
491. NeurIPS 2025Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning
492. NeurIPS 2025Progress Reward Model for Reinforcement Learning via Large Language Models
493. NeurIPS 2025Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs
494. NeurIPS 2025Prompt Tuning Decision Transformers with Structured and Scalable Bandits
495. NeurIPS 2025Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs
496. NeurIPS 2025ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
497. NeurIPS 2025ProtoPairNet: Interpretable Regression through Prototypical Pair Reasoning
498. NeurIPS 2025Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents
499. NeurIPS 2025Provably Efficient Online RLHF with One-Pass Reward Modeling
500. NeurIPS 2025Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation

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.