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

1,827 papers, page 35 of 37

1701. ICLR 2023Learning About Progress From Experts
1702. ICLR 2023Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward
1703. ICLR 2023Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
1704. ICLR 2023Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
1705. ICLR 2023Learning Simultaneous Navigation and Construction in Grid Worlds
1706. ICLR 2023Learning Soft Constraints From Constrained Expert Demonstrations
1707. ICLR 2023Learning to Segment from Noisy Annotations: A Spatial Correction Approach
1708. ICLR 2023Learning Uncertainty for Unknown Domains with Zero-Target-Assumption
1709. ICLR 2023Learning Zero-Shot Cooperation with Humans, Assuming Humans Are Biased
1710. ICLR 2023Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies
1711. ICLR 2023LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
1712. ICLR 2023MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection
1713. ICLR 2023MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning
1714. ICLR 2023Making Better Decision by Directly Planning in Continuous Control
1715. ICLR 2023ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
1716. ICLR 2023Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
1717. ICLR 2023Memory Gym: Partially Observable Challenges to Memory-Based Agents
1718. ICLR 2023Mind the Gap: Offline Policy Optimization for Imperfect Rewards
1719. ICLR 2023Minimax Optimal Kernel Operator Learning via Multilevel Training
1720. ICLR 2023Minimum Description Length Control
1721. ICLR 2023Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach
1722. ICLR 2023MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations
1723. ICLR 2023More Centralized Training, Still Decentralized Execution: Multi-Agent Conditional Policy Factorization
1724. ICLR 2023Multi-Objective Reinforcement Learning: Convexity, Stationarity and Pareto Optimality
1725. ICLR 2023Multi-skill Mobile Manipulation for Object Rearrangement
1726. ICLR 2023Near-Optimal Adversarial Reinforcement Learning with Switching Costs
1727. ICLR 2023Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
1728. ICLR 2023Near-optimal Policy Identification in Active Reinforcement Learning
1729. ICLR 2023Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
1730. ICLR 2023Neural Agents Struggle to Take Turns in Bidirectional Emergent Communication
1731. ICLR 2023Neural DAG Scheduling via One-Shot Priority Sampling
1732. ICLR 2023Neural Episodic Control with State Abstraction
1733. ICLR 2023Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery
1734. ICLR 2023Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes
1735. ICLR 2023Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling
1736. ICLR 2023Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
1737. ICLR 2023Offline RL for Natural Language Generation with Implicit Language Q Learning
1738. ICLR 2023Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization
1739. ICLR 2023On the Data-Efficiency with Contrastive Image Transformation in Reinforcement Learning
1740. ICLR 2023On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning
1741. ICLR 2023On the Robustness of Safe Reinforcement Learning under Observational Perturbations
1742. ICLR 2023On the Sensitivity of Reward Inference to Misspecified Human Models
1743. ICLR 2023Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
1744. ICLR 2023Optimal Transport for Offline Imitation Learning
1745. ICLR 2023Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics
1746. ICLR 2023Order Matters: Agent-by-agent Policy Optimization
1747. ICLR 2023Outcome-directed Reinforcement Learning by Uncertainty \& Temporal Distance-Aware Curriculum Goal Generation
1748. ICLR 2023PAC Reinforcement Learning for Predictive State Representations
1749. ICLR 2023Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms
1750. ICLR 2023PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm

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.