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

2,494 papers, page 12 of 50

551. NeurIPS 2026RILA: A Radar-Native Structured Interface from Sparse mmWave Point Clouds to Large Language Models
552. NeurIPS 2026Risk-Aware Action Repetition via Expected Skip Evaluation
553. NeurIPS 2026Risk-Controlled Post-Processing of Decision Policies
554. NeurIPS 2026Risk-Sensitive Deep Optimal Stopping
555. NeurIPS 2026RL Excursions during Pre-training: How early is too early for on-policy learning?
556. NeurIPS 2026RL-Guided Contraction of Symbolic Tensor Networks for Quantum Circuit Equivalence
557. NeurIPS 2026RL-Guided Temporal Localization for Dual-Channel Retrieval in Long-Horizon Agent Memory
558. NeurIPS 2026RL-Inf: Tracking Non-local Training Data Influence for Online Reinforcement Learning
559. NeurIPS 2026RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
560. NeurIPS 2026Robust Offline Reinforcement Learning against Out-of-Distribution Dynamics in Autonomous Driving
561. NeurIPS 2026Robust Policy Optimization to Prevent Catastrophic Forgetting
562. NeurIPS 2026Robust Stream Classification using Time Neutralising Decision Trees
563. NeurIPS 2026Robust-by-Design Distributional Learning from Contaminated Samples
564. NeurIPS 2026ROLLVERIFY: BRIDGING EFFICIENCY AND ACCURACY IN LONG-TAIL ROLLOUT REINFORCEMENT LEARNING
565. NeurIPS 2026Rotations on Latent Hyperspheres: a Geometry-Aware Guiding Framework for Diffusion Models
566. NeurIPS 2026Rubric-Align: Safety Alignment through Dynamically Co-Evolving Rubrics
567. NeurIPS 2026S$^2$-RL: Sample-Set Dual Reinforcement Learning for Generative Semantic Segmentation Dataset Distillation
568. NeurIPS 2026S2T-RLHF: Hierarchical Credit Assignment for Stable Preference-Based RLHF
569. NeurIPS 2026Safe Offline Reinforcement Learning using Behavior Regularisation and Latent Feasibility-Guidance
570. NeurIPS 2026Safe Score Matching: Diffusion Policies with Hamilton-Jacobi Reachability for Online Safe Reinforcement Learning
571. NeurIPS 2026Safe-Fair MACPO: Burden-Fair Constrained Policy Optimization for Safe Multi-Agent Reinforcement Learning
572. NeurIPS 2026SafePro: Generation of Safe and Functional Proteins via Cross-Task Conflict-Aware Alignment
573. NeurIPS 2026SAIR: Cost-Efficient Multi-Stage ML Pipeline Autoscaling via In-Context Reinforcement Learning
574. NeurIPS 2026Same Words, Different Judgments: How Preferences Vary Across Modalities
575. NeurIPS 2026Sampling-Based Safe Reinforcement Learning
576. NeurIPS 2026SAMPPO: Structure-Aware Mirror Proximal Policy Optimization
577. NeurIPS 2026Scalable Minimal-Change Learning for Controllable Image Editing
578. NeurIPS 2026Scalable Multi-Agent Contrastive Reinforcement Learning
579. NeurIPS 2026SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics
580. NeurIPS 2026Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models
581. NeurIPS 2026SD-Search: Hindsight Self-Distillation for Search-Augmented Reasoning
582. NeurIPS 2026SEAR: Sample Efficient Action Chunking Reinforcement Learning
583. NeurIPS 2026Seeing but Not Detecting: Privacy-Preserving Scene Text Attack via Hybrid Adversarial Policy Learning
584. NeurIPS 2026Selective Off-Policy Reference Tuning with Plan Guidance
585. NeurIPS 2026Self-Calibrated GUI Reward Model via Inverse Dynamic Modeling
586. NeurIPS 2026Self-Correction as Transition Geometry: Internalizing Reasoning via Lifted State Policy Optimization
587. NeurIPS 2026Self-Distilled RLVR
588. NeurIPS 2026Self-Evolution Reasoner: Continuous Optimization via Policy-Intrinsic Exploration and Exploitation
589. NeurIPS 2026Self-Evolving Agents Should Build Internal and External Models of the World
590. NeurIPS 2026Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets
591. NeurIPS 2026Self-Supervised On-Policy Reinforcement Learning via Contrastive Proximal Policy Optimisation
592. NeurIPS 2026SelfCritic-VLA: Language as Intrinsic Critic for Vision Language Action Models in Autonomous Driving
593. NeurIPS 2026Serialization Tax in Shared-Latent Exchangeable Decisions
594. NeurIPS 2026SETA: Scaling Environments for Terminal Agents
595. NeurIPS 2026SFT-then-RL Outperforms Mixed-Policy Methods for LLM Reasoning
596. NeurIPS 2026Shared Modular Recurrence in Contextual MDPs for Universal Morphology Control
597. NeurIPS 2026Sharper Guarantees for Misspecified Kernelized Bandit Optimization
598. NeurIPS 2026Signal-Adaptive Trust Regions for Gradient-Free Optimization of Recurrent Spiking Neural Networks
599. NeurIPS 2026Simulating Students or Sycophantic Problem Solving? On Misconception Faithfulness of LLM Simulators
600. NeurIPS 2026Simulation-aided Reinforcement Learning with Control Variates

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.