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

6,885 papers, page 131 of 138

6501. NeurIPS 2023De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
6502. NeurIPS 2023Debiased and Denoised Entity Recognition from Distant Supervision
6503. NeurIPS 2023Debiasing Conditional Stochastic Optimization
6504. NeurIPS 2023Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models
6505. NeurIPS 2023Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
6506. NeurIPS 2023Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning
6507. NeurIPS 2023Deep Reinforcement Learning with Plasticity Injection
6508. NeurIPS 2023DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
6509. NeurIPS 2023Design from Policies: Conservative Test-Time Adaptation for Offline Policy Optimization
6510. NeurIPS 2023DIFFER:Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
6511. NeurIPS 2023Diffused Task-Agnostic Milestone Planner
6512. NeurIPS 2023Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning
6513. NeurIPS 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Model
6514. NeurIPS 2023Direct Preference-based Policy Optimization without Reward Modeling
6515. NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
6516. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
6517. NeurIPS 2023Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
6518. NeurIPS 2023Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
6519. NeurIPS 2023Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
6520. NeurIPS 2023Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning
6521. NeurIPS 2023Diversify \& Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement
6522. NeurIPS 2023Domain Adaptive Imitation Learning with Visual Observation
6523. NeurIPS 2023Double Gumbel Q-Learning
6524. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
6525. NeurIPS 2023Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
6526. NeurIPS 2023DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
6527. NeurIPS 2023Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL
6528. NeurIPS 2023DynaDojo: An Extensible Benchmarking Platform for Scalable Dynamical System Identification
6529. NeurIPS 2023Dynamic Regret of Adversarial Linear Mixture MDPs
6530. NeurIPS 2023Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
6531. NeurIPS 2023Easy Learning from Label Proportions
6532. NeurIPS 2023Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
6533. NeurIPS 2023Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning
6534. NeurIPS 2023Efficient Diffusion Policies For Offline Reinforcement Learning
6535. NeurIPS 2023Efficient Exploration in Continuous-time Model-based Reinforcement Learning
6536. NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
6537. NeurIPS 2023Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization
6538. NeurIPS 2023Efficient Model-Free Exploration in Low-Rank MDPs
6539. NeurIPS 2023Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
6540. NeurIPS 2023Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric
6541. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
6542. NeurIPS 2023Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
6543. NeurIPS 2023Elastic Decision Transformer
6544. NeurIPS 2023ELDEN: Exploration via Local Dependencies
6545. NeurIPS 2023Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback
6546. NeurIPS 2023End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
6547. NeurIPS 2023Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
6548. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
6549. NeurIPS 2023Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
6550. NeurIPS 2023Explore to Generalize in Zero-Shot RL

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.