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

1,021 papers, page 10 of 21

451. ICML 2026Landmark-Guided Policy Optimization for Multi-Objective Language Model Selection
452. ICML 2026Langevin Rollout Optimization for Modelic Reinforcement Learning
453. ICML 2026Language-based Trial and Error Falls Behind in the Era of Experience
454. ICML 2026Laplacian Representations for Decision-Time Planning
455. ICML 2026LARFT: Closing the Cognition-Action Gap for Length Instruction Following in Large Language Models
456. ICML 2026LASER: Learning Active Sensing for Continuum Field Reconstruction
457. ICML 2026Latent Guided Sampling for Combinatorial Optimization
458. ICML 2026Latent Reasoning in TRMs is Secretly a Policy Improvement Operator
459. ICML 2026Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
460. ICML 2026Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
461. ICML 2026Lavida-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models
462. ICML 2026Learn from A Rationalist: Distilling Intermediate Interpretable Rationales
463. ICML 2026Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs
464. ICML 2026Learn to change the world: Multi-level reinforcement learning with model-changing actions
465. ICML 2026Learning Anisotropic Value Geometry with Finsler Reinforcement Learning
466. ICML 2026Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
467. ICML 2026Learning Disentangled Multi-Agent World Model for Decentralized Control
468. ICML 2026Learning from Comparison: Constrained Projection Policy Optimization for Pareto-Front Improvement
469. ICML 2026Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL
470. ICML 2026Learning GUI Grounding with Spatial Reasoning from Visual Feedback
471. ICML 2026Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
472. ICML 2026Learning Interpretable Options by Identifying Reward Diffusion Bottlenecks in Reinforcement Learning
473. ICML 2026Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
474. ICML 2026Learning Permutation from Structure Without Supervision
475. ICML 2026Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory
476. ICML 2026Learning Rate Scaling across LoRA Ranks and Transfer to Full Finetuning
477. ICML 2026Learning Reward–Cost Balance in Safe RL via Score-Based World Models
478. ICML 2026Learning Robust Multi-Agent Policies via Selective Adversarial Fault Induction
479. ICML 2026Learning Self-Correction in Vision–Language Models via Rollout Augmentation
480. ICML 2026Learning Structured Reasoning via Tractable Trajectory Control
481. ICML 2026Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling
482. ICML 2026Learning the Best Under Constraints: A Duality-Based Framework
483. ICML 2026Learning the Minimum Action Distance
484. ICML 2026Learning to Approximate Uniform Facility Location via Graph Neural Networks
485. ICML 2026Learning to Bet for Horizon-Aware Anytime-Valid Testing
486. ICML 2026Learning to Correct: Reinforcement Learning for Multi-Attempt Chain-of-Thought
487. ICML 2026Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models
488. ICML 2026Learning to Discover at Test Time
489. ICML 2026Learning to Evict from Key-Value Cache
490. ICML 2026Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization
491. ICML 2026Learning to Perceive the World Through Control: Empowerment-Based Representation Learning
492. ICML 2026Learning to Rank from Incomplete Rankings
493. ICML 2026Learning to Reason for Factuality
494. ICML 2026Learning to Reconfigure: Configuration-Control Co-optimization of Reconfigurable Robots for Heterogeneous Locomotion
495. ICML 2026Learning to Route Languages for Multilingual Policy Optimization
496. ICML 2026Learning to Search and Searching to Learn for Generalization in Planning
497. ICML 2026Learning to Self-Verify Makes Language Models Better Reasoners
498. ICML 2026Learning to Share: Selective Memory for Efficient Parallel Agentic Systems
499. ICML 2026Learning to Watch: Active Video Anomaly Understanding via Interleaved Policy Optimization
500. ICML 2026Learning Transferable Interaction Primitives from Game Videos for Humanoid Locomotion

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.