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

2,985 papers, page 50 of 60

2451. NeurIPS 2026Extracting Training Data from Diffusion Language Models via Infilling
2452. NeurIPS 2026Fair Range k-Supplier Clustering in Offline and Streaming Models
2453. NeurIPS 2026Finetuning with Sampling: Make SFT Generalize, Not Forget
2454. NeurIPS 2026Finite Time Analysis of Risk-Sensitive RL via Noisy Power Iteration
2455. NeurIPS 2026Finite-Resolution Decision Sufficiency for Linear Optimization
2456. NeurIPS 2026Finite-Sample Convergence in Networked Average Reward MARL: Decentralization Pitfalls and Entropy Remedies
2457. NeurIPS 2026FiRe: Fine-grained Multimodal Reasoning for Enhanced Image Generation
2458. NeurIPS 2026Fisher-Glass: Tail Sample Complexity from Nuisance-Projected Fisher Information
2459. NeurIPS 2026Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing
2460. NeurIPS 2026FLAG: Flow Policy MaxEnt-RL by Latent Augmented Guidance
2461. NeurIPS 2026Flow Matching for Offline Reinforcement Learning with Discrete Actions
2462. NeurIPS 2026Flow Matching Policy Optimization with Mirror Descent and Entropy Constraints
2463. NeurIPS 2026Flow Matching Reinforcement Learning via SDE Inference
2464. NeurIPS 2026Flow-DPPO: Divergence Proximal Policy Optimization for Flow Matching Models
2465. NeurIPS 2026FlowSteer: Towards Agents Designing Agentic Workflows via Reinforced Progressive Canvas Editing
2466. NeurIPS 2026Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
2467. NeurIPS 2026Focusing Influence Mechanism for Multi-Agent Reinforcement Learning
2468. NeurIPS 2026Forgetting to Improve: Principled Data Removal in Active Learning
2469. NeurIPS 2026Forward Shapley Scoring for Non-Myopic Active Feature Acquisition
2470. NeurIPS 2026FoundSurface: Feedforward Ray-Based 3D Scene Surface Reconstruction from Unposed Images
2471. NeurIPS 2026FracEncoder: Towards Adaptive Cognitive Trajectories via Fractional-Order Context Encoding
2472. NeurIPS 2026From Anti-Forgetting to Fast Adaptation: Continual Reinforcement Learning with World Models
2473. NeurIPS 2026From Approximation to Computation: Universal Power of Deep Narrow Networks at Constant Width
2474. NeurIPS 2026From Expert Knowledge to Optimization Modeling: Prototype-Based Data Synthesis and Logical Reinforcement Learning
2475. NeurIPS 2026From Ideas to Code: Tree-structured Policy Optimization for Automated Algorithm Design with LLMs
2476. NeurIPS 2026From POMDP Theory to Deep RL with Particle Filters
2477. NeurIPS 2026From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
2478. NeurIPS 2026From Sample to Subset Construction: Coverage-Aware Curation of Robot Demonstrations
2479. NeurIPS 2026From Structural Feedback to Prompt Policies: Learning Faithful Text-to-Image Prompt Editors
2480. NeurIPS 2026From Views to Worlds: Active Exploration over 3D Worlds for Vision-Language Models
2481. NeurIPS 2026FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning
2482. NeurIPS 2026GARDO: Reinforcing Diffusion Models without Reward Hacking
2483. NeurIPS 2026GCD: Correcting Hidden-State Bias in Off-Policy Agentic RL
2484. NeurIPS 2026GDMD: Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning
2485. NeurIPS 2026GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
2486. NeurIPS 2026Gen-Searcher: Reinforcing Agentic Search for Image Generation
2487. NeurIPS 2026Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions
2488. NeurIPS 2026Generalized Intention Modeling in Multi-Agent Reinforcement Learning
2489. NeurIPS 2026Generation Navigator: A State-Aware Agentic Framework for Image Generation
2490. NeurIPS 2026Generative Actor-Critic with Soft Bridge Policies
2491. NeurIPS 2026Generative Scenario Rollouts for End-to-End Autonomous Driving
2492. NeurIPS 2026GeoSym127K: Scalable Symbolically-verifiable Synthesis for Multimodal Geometric Reasoning
2493. NeurIPS 2026GeoX: Mastering Geospatial Reasoning Through Self-Play and Verifiable Rewards
2494. NeurIPS 2026GNES: Neural-Guided Evolutionary Program Search for Interpretable Multi-Agent Control
2495. NeurIPS 2026Gradient Routing Localizes and Removes Unintended Behaviors in RL
2496. NeurIPS 2026Graph Topology Augmentation for Prioritized Sweeping in Non-stationary Reinforcement Learning
2497. NeurIPS 2026GraphMemRL: Action-Native Reinforcement Learning for Persistent Graph Memory Construction
2498. NeurIPS 2026Grounding Agent Reasoning with Structured Process Supervision for Multi-turn Reinforcement Learning
2499. NeurIPS 2026Grounding Multimodal Reasoning with Evidence-Ablated Negatives
2500. NeurIPS 2026Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning

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.