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

2,079 papers, page 33 of 42

1601. ICML 2024MaxMin-RLHF: Alignment with Diverse Human Preferences
1602. ICML 2024Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning
1603. ICML 2024Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
1604. ICML 2024Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
1605. ICML 2024Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary
1606. ICML 2024Mixtures of Experts Unlock Parameter Scaling for Deep RL
1607. ICML 2024MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation
1608. ICML 2024Model-based Reinforcement Learning for Confounded POMDPs
1609. ICML 2024Model-based Reinforcement Learning for Parameterized Action Spaces
1610. ICML 2024Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
1611. ICML 2024Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
1612. ICML 2024Mollification Effects of Policy Gradient Methods
1613. ICML 2024Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
1614. ICML 2024More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
1615. ICML 2024Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
1616. ICML 2024Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
1617. ICML 2024Multi-View Clustering by Inter-cluster Connectivity Guided Reward
1618. ICML 2024MusicRL: Aligning Music Generation to Human Preferences
1619. ICML 2024Nash Learning from Human Feedback
1620. ICML 2024Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
1621. ICML 2024Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
1622. ICML 2024Neural-Kernel Conditional Mean Embeddings
1623. ICML 2024No-Regret Reinforcement Learning in Smooth MDPs
1624. ICML 2024Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation
1625. ICML 2024Nonlinear Filtering with Brenier Optimal Transport Maps
1626. ICML 2024ODIN: Disentangled Reward Mitigates Hacking in RLHF
1627. ICML 2024Offline Actor-Critic Reinforcement Learning Scales to Large Models
1628. ICML 2024Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
1629. ICML 2024Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms
1630. ICML 2024Offline Multi-Objective Optimization
1631. ICML 2024Offline Transition Modeling via Contrastive Energy Learning
1632. ICML 2024Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
1633. ICML 2024OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning
1634. ICML 2024OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
1635. ICML 2024On the Second-Order Convergence of Biased Policy Gradient Algorithms
1636. ICML 2024On The Statistical Complexity of Offline Decision-Making
1637. ICML 2024On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation
1638. ICML 2024On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective
1639. ICML 2024Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning
1640. ICML 2024Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
1641. ICML 2024OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videos
1642. ICML 2024Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks
1643. ICML 2024Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
1644. ICML 2024Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
1645. ICML 2024Pausing Policy Learning in Non-stationary Reinforcement Learning
1646. ICML 2024PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
1647. ICML 2024Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
1648. ICML 2024Pi-DUAL: Using privileged information to distinguish clean from noisy labels
1649. ICML 2024PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
1650. ICML 2024PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling

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.