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 49 of 60

2401. NeurIPS 2026Distribution Corrected Decision Transformer for Offline Reinforcement Learning with Imbalanced Datasets
2402. NeurIPS 2026Distribution-Adaptive Policy Optimization
2403. NeurIPS 2026Distributionally Robust Black Box Optimization-based Bidding Strategy in Auction-based Federated Learning
2404. NeurIPS 2026Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
2405. NeurIPS 2026Distributionally Robust Token Optimization in RLHF
2406. NeurIPS 2026Distributionally-Robust Policy Learning from Observational Data
2407. NeurIPS 2026DiversePlace: Diversity-Seeking Curriculum Reinforcement Learning for Macro Placement
2408. NeurIPS 2026DocAtlas: Long-Document Understanding as Mutable-State Interaction
2409. NeurIPS 2026Dodge-It: Learning Collision-Aware VLA Models for Robotic Manipulation
2410. NeurIPS 2026Don’t Let Gains FADE: Breaking Down Policy Gradient Weights in RL
2411. NeurIPS 2026DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training
2412. NeurIPS 2026Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems
2413. NeurIPS 2026Drift Q-Learning
2414. NeurIPS 2026Drifting Field Policy: Wasserstein Gradient Flow on Policy Space for Offline-to-Online RL
2415. NeurIPS 2026DRILL: Training World Models to Improve Policies, Not Predict Pixels
2416. NeurIPS 2026DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation
2417. NeurIPS 2026DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts
2418. NeurIPS 2026DUDS: Dual-stage Data Selection for Efficient Reinforcement Learning with Verifiable Rewards
2419. NeurIPS 2026Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty
2420. NeurIPS 2026DynamAuction: a reinforcement learning environment for repeated auction with dynamic value
2421. NeurIPS 2026Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer
2422. NeurIPS 2026Dynamic Treatment on Networks
2423. NeurIPS 2026Dynamics-Informed Adaptive Offline RL for Real-Time Tokamak Plasma Control
2424. NeurIPS 2026Early Prediction of Future Behavioral Strategy from Process Traces
2425. NeurIPS 2026ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning
2426. NeurIPS 2026Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing
2427. NeurIPS 2026Effectiveness of Curriculum Learning Depends on Reward Sparsity and Competing Optima
2428. NeurIPS 2026Efficient Diffusion Policy Fine Tuning with Latent Noise Representation Bridging
2429. NeurIPS 2026Efficient Gradient-Aware Asynchronous Reinforcement Learning for LLM Post-Training
2430. NeurIPS 2026Efficient Off-Policy RL for Video Generation via Forward-Consistent Reward Matching
2431. NeurIPS 2026Efficient Test-Time Adaptation For Robot Policies
2432. NeurIPS 2026EfficientRollout: System-Aware Self-Speculative Decoding for RL Rollouts
2433. NeurIPS 2026Enhancing Speech Large Language Models through Reinforced Behavior Alignment
2434. NeurIPS 2026Entropy Dynamics of Agent Reinforcement Learning
2435. NeurIPS 2026Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
2436. NeurIPS 2026Error-Guided Bellman Calibration for Semi-Offline Value Estimation
2437. NeurIPS 2026Escaping Path Mirages in Offline Goal-Conditioned Reinforcement Learning
2438. NeurIPS 2026ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning
2439. NeurIPS 2026EventLens: Event-Structure Reinforcement Learning for Video Understanding
2440. NeurIPS 2026EvoGround: Self-Evolving Video Agents for Video Temporal Grounding
2441. NeurIPS 2026Evolutionary System Prompt Learning for Reinforcement Learning in LLMs
2442. NeurIPS 2026EvoMM: Reinforced Self-Evolving Multimodal Agentic Memory
2443. NeurIPS 2026EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modeling
2444. NeurIPS 2026Expanding LLM Agent Boundaries with Strategy-Guided Exploration
2445. NeurIPS 2026Explaining and Preventing Alignment Collapse in Iterative RLHF
2446. NeurIPS 2026ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection
2447. NeurIPS 2026Exploration as Constrained Policy-Space Optimization
2448. NeurIPS 2026Exploration via Exploitation: The Blessing of Reward Diversity in Personalized Federated RL
2449. NeurIPS 2026Exploring Lifelong Adaptation: In-Context Reinforcement Learning in Non-Stationary Environments
2450. NeurIPS 2026Exploring Starts Are Not Enough: Counterexamples and a Fix for Monte Carlo Exploring Starts

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.