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

6,885 papers, page 32 of 138

1551. ICML 2026Functional building blocks of neural networks: from network motifs to collective dynamics
1552. ICML 2026G$^2$RPO: Geometric GRPO; Escaping LLM's Reasoning Rut to Break Accuracy--Entropy Trade-off
1553. ICML 2026GameVerse: Can Vision-Language Models Learn from Video-based Reflection?
1554. ICML 2026GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
1555. ICML 2026GenAlign: Towards Unified Alignment Framework of MLLMs via Generative Reward Model
1556. ICML 2026GenCircuit-RL: Reinforcement Learning from Hierarchical Verification for Genetic Circuit Design
1557. ICML 2026Generative Online Reinforcement Learning
1558. ICML 2026GeoAlign: Geometric Rollout Curation for Robust LLM Reinforcement Learning
1559. ICML 2026Geometric Coherence Learning for Structuring Value Functions in Plain MDPs
1560. ICML 2026Geometric Control of Out-of-Distribution Shift in Safe Offline RL
1561. ICML 2026Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR
1562. ICML 2026GIPO: Gaussian Importance Sampling Policy Optimization
1563. ICML 2026GLARE: Scalable Neuro-Symbolic Reward Shaping for LLM Agents via Group-Level Automata
1564. ICML 2026Global Policy-Space Response Oracles for Two-Player Zero-Sum Games
1565. ICML 2026Goal-Conditioned Agents that Learn Everything All at Once
1566. ICML 2026Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text
1567. ICML 2026Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning
1568. ICML 2026Gradient Regularization Mitigates Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
1569. ICML 2026Gradient-Aware Scheduling: Coupling Curriculum and Staleness for Async Reinforcement Learning
1570. ICML 2026Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity
1571. ICML 2026GradientStabilizer: Fix the Norm, Not the Gradient
1572. ICML 2026Graph-GRPO: Training Graph Flow Models with Reinforcement Learning
1573. ICML 2026Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning
1574. ICML 2026GRASP: Graph Reasoning via Agentic Solving and Probing of LLMs
1575. ICML 2026Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs
1576. ICML 2026Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
1577. ICML 2026Group Distributionally Robust Optimization-Driven RL for LLM Reasoning
1578. ICML 2026GRPO is Secretly a Process Reward Model
1579. ICML 2026GRPO-based Cluster Decision Agent for Unknown-$\boldsymbol{K}$ Multi-view Clustering
1580. ICML 2026GTPO and GRPO-S: Token and Sequence-Level Reward Shaping with Policy Entropy
1581. ICML 2026GUI-Spotlight: Adaptive Iterative Focus Refinement for Enhanced GUI Visual Grounding
1582. ICML 2026GXPO: Group Cross-Lingual Relative Policy Optimization for Code Generation
1583. ICML 2026Hard labels sampled from sparse targets mislead rotation invariant algorithms
1584. ICML 2026Harmonized Dual Policy Improvement for Modelic Reinforcement Learning
1585. ICML 2026Harnessing Uncertainty: Entropy-Modulated Policy Gradients for Long-Horizon LLM Agents
1586. ICML 2026HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
1587. ICML 2026Hierarchical Decision Making with Structured Policies: A Principled Design via Inverse Optimization
1588. ICML 2026Hierarchical Goal Abstractions via Learned Subset Relations
1589. ICML 2026Hierarchical Reinforcement Learning for Sparse-Reward Search in Commutative Algebra
1590. ICML 2026Hierarchical Successor Representation for Robust Transfer
1591. ICML 2026HiMAP-Travel: Hierarchical Multi-Agent Planning for Long-Horizon Constrained Travel
1592. ICML 2026HiPER: Hierarchical Plan–Execute RL for Multi-Turn LLM Agents
1593. ICML 2026Hista and Numca: Estimate State Value Effectively for Large Language Model Reinforcement Learning
1594. ICML 2026HodgeFlow Policy Search by Topologically Dissecting Temporal-Difference Signals in Non-Markovian Environments
1595. ICML 2026HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
1596. ICML 2026Holonomy Grid Codes for Generalisation Under Directed Actions
1597. ICML 2026How Does Reasoning Flow? Tracing Attention-Induced Information Flow for Targeted RL in LLMs
1598. ICML 2026How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
1599. ICML 2026How Reasoning Evolves from Post-Training Data: An Empirical Study Using Chess
1600. ICML 2026How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning

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.