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 56 of 60

2751. NeurIPS 2026Reinforcement Learning for Diffusion LLMs with Entropy-Guided Step Selection and Stepwise Advantages
2752. NeurIPS 2026Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
2753. NeurIPS 2026Reinforcement Learning for View-Adaptive Distillation in 3D Gaussian Compression
2754. NeurIPS 2026Reinforcement Learning with Multi-Step Lookahead Information Via Adaptive Batching
2755. NeurIPS 2026Reinforcement Learning with Verifiable Physics: Post-training LLMs for PDE Solver Generation
2756. NeurIPS 2026Reinforcing Multimodal Reasoning Against Visual Degradation
2757. NeurIPS 2026Replay-buffer engineering for noise-robust quantum circuit optimization
2758. NeurIPS 2026Representation Learning Enables Scalable Multitask Deep Reinforcement Learning
2759. NeurIPS 2026Residual Expertise Is Not Decision Value
2760. NeurIPS 2026Rethinking "RL Generalizes, SFT Memorizes": The Role of SFT Data
2761. NeurIPS 2026Rethinking Learning from Label Proportions via Moment Matching
2762. NeurIPS 2026Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting
2763. NeurIPS 2026Rethinking Ratio-Based Trust Regions for Policy Optimization in Multi-Agent Reinforcement Learning
2764. NeurIPS 2026RevengeBench: Reverse Engineering Code-Space Policies from Behavioral Experiments
2765. NeurIPS 2026Reverse to Advance: Teleoperation-Cost Effective Hard Policy Learning from Reversed Easy Tasks
2766. NeurIPS 2026REVERSE: Reinforcing Evidence Verification and Search for Agentic Image Geolocation
2767. NeurIPS 2026Revisiting Value Iteration: Unified Analysis of Discounted and Average-Reward Cases
2768. NeurIPS 2026Reward Hacking in Rubric-Based Reinforcement Learning
2769. NeurIPS 2026Reward Inflation: A Healthy Stimulus for Reinforcement Learning
2770. NeurIPS 2026Reward Is Not a Universal Interface for Generative Reinforcement Learning
2771. NeurIPS 2026Reward Shaping to Improve Language Model Query Generation
2772. NeurIPS 2026Reward-Conditioned Reinforcement Learning
2773. NeurIPS 2026Reward-Estimated Hypergradient for Bilevel Reinforcement Learning with Black-Box Follower
2774. NeurIPS 2026RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with LLMs
2775. NeurIPS 2026Rich Insights from Cheap Signals: Efficient Evaluations via Tensor Factorization
2776. NeurIPS 2026RILA: A Radar-Native Structured Interface from Sparse mmWave Point Clouds to Large Language Models
2777. NeurIPS 2026Risk-Aware Action Repetition via Expected Skip Evaluation
2778. NeurIPS 2026Risk-Controlled Post-Processing of Decision Policies
2779. NeurIPS 2026Risk-Sensitive Deep Optimal Stopping
2780. NeurIPS 2026RL Excursions during Pre-training: How early is too early for on-policy learning?
2781. NeurIPS 2026RL-Guided Contraction of Symbolic Tensor Networks for Quantum Circuit Equivalence
2782. NeurIPS 2026RL-Guided Temporal Localization for Dual-Channel Retrieval in Long-Horizon Agent Memory
2783. NeurIPS 2026RL-Inf: Tracking Non-local Training Data Influence for Online Reinforcement Learning
2784. NeurIPS 2026RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
2785. NeurIPS 2026Robust Offline Reinforcement Learning against Out-of-Distribution Dynamics in Autonomous Driving
2786. NeurIPS 2026Robust Policy Optimization to Prevent Catastrophic Forgetting
2787. NeurIPS 2026Robust Stream Classification using Time Neutralising Decision Trees
2788. NeurIPS 2026Robust-by-Design Distributional Learning from Contaminated Samples
2789. NeurIPS 2026ROLLVERIFY: BRIDGING EFFICIENCY AND ACCURACY IN LONG-TAIL ROLLOUT REINFORCEMENT LEARNING
2790. NeurIPS 2026Rotations on Latent Hyperspheres: a Geometry-Aware Guiding Framework for Diffusion Models
2791. NeurIPS 2026Rubric-Align: Safety Alignment through Dynamically Co-Evolving Rubrics
2792. NeurIPS 2026S$^2$-RL: Sample-Set Dual Reinforcement Learning for Generative Semantic Segmentation Dataset Distillation
2793. NeurIPS 2026S2T-RLHF: Hierarchical Credit Assignment for Stable Preference-Based RLHF
2794. NeurIPS 2026Safe Offline Reinforcement Learning using Behavior Regularisation and Latent Feasibility-Guidance
2795. NeurIPS 2026Safe Score Matching: Diffusion Policies with Hamilton-Jacobi Reachability for Online Safe Reinforcement Learning
2796. NeurIPS 2026Safe-Fair MACPO: Burden-Fair Constrained Policy Optimization for Safe Multi-Agent Reinforcement Learning
2797. NeurIPS 2026SafePro: Generation of Safe and Functional Proteins via Cross-Task Conflict-Aware Alignment
2798. NeurIPS 2026SAIR: Cost-Efficient Multi-Stage ML Pipeline Autoscaling via In-Context Reinforcement Learning
2799. NeurIPS 2026Same Words, Different Judgments: How Preferences Vary Across Modalities
2800. NeurIPS 2026Sampling-Based Safe Reinforcement Learning

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.