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 31 of 42

1501. ICML 2024EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
1502. ICML 2024Emergence of In-Context Reinforcement Learning from Noise Distillation
1503. ICML 2024End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
1504. ICML 2024Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
1505. ICML 2024Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning
1506. ICML 2024Environment Design for Inverse Reinforcement Learning
1507. ICML 2024EvIL: Evolution Strategies for Generalisable Imitation Learning
1508. ICML 2024EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
1509. ICML 2024Exploration and Anti-Exploration with Distributional Random Network Distillation
1510. ICML 2024Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
1511. ICML 2024Exploring the LLM Journey from Cognition to Expression with Linear Representations
1512. ICML 2024Factored-Reward Bandits with Intermediate Observations
1513. ICML 2024Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models
1514. ICML 2024Fair Off-Policy Learning from Observational Data
1515. ICML 2024Fair Resource Allocation in Multi-Task Learning
1516. ICML 2024Fast Decision Boundary based Out-of-Distribution Detector
1517. ICML 2024Feasibility Consistent Representation Learning for Safe Reinforcement Learning
1518. ICML 2024Feasible Reachable Policy Iteration
1519. ICML 2024Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices
1520. ICML 2024Feedback Efficient Online Fine-Tuning of Diffusion Models
1521. ICML 2024FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
1522. ICML 2024Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
1523. ICML 2024Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
1524. ICML 2024Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
1525. ICML 2024Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
1526. ICML 2024Foundation Policies with Hilbert Representations
1527. ICML 2024Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
1528. ICML 2024From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
1529. ICML 2024From Generalization Analysis to Optimization Designs for State Space Models
1530. ICML 2024From Inverse Optimization to Feasibility to ERM
1531. ICML 2024From Neurons to Neutrons: A Case Study in Interpretability
1532. ICML 2024From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
1533. ICML 2024From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
1534. ICML 2024Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees
1535. ICML 2024Fundamental Limitations of Alignment in Large Language Models
1536. ICML 2024FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
1537. ICML 2024Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction
1538. ICML 2024GFlowNet Training by Policy Gradients
1539. ICML 2024Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods
1540. ICML 2024Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling
1541. ICML 2024HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning
1542. ICML 2024HarmonyDream: Task Harmonization Inside World Models
1543. ICML 2024HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
1544. ICML 2024HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming
1545. ICML 2024Hieros: Hierarchical Imagination on Structured State Space Sequence World Models
1546. ICML 2024How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
1547. ICML 2024How Does Goal Relabeling Improve Sample Efficiency?
1548. ICML 2024How to Explore with Belief: State Entropy Maximization in POMDPs
1549. ICML 2024How to Leverage Diverse Demonstrations in Offline Imitation Learning
1550. ICML 2024Human Alignment of Large Language Models through Online Preference Optimisation

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.