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 13 of 50

601. NeurIPS 2026SIRAS: Sibling-Relative Advantage Shaping for Reinforcement Learning from Verifiable Rewards
602. NeurIPS 2026Skill-Coupled Policy Optimization with Calibrated Group-Wise Advantage Estimation
603. NeurIPS 2026Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents
604. NeurIPS 2026SkillForge: Co-Evolving Skills and Agents via Dynamic Skill Lifecycles
605. NeurIPS 2026SLOPE: Optimistic Potential Landscape Shaping for Model-based Reinforcement Learning
606. NeurIPS 2026Smart Picks in the Dark: Towards Efficient RLVR for Reasoning via Tracing Metacognitive Pivots
607. NeurIPS 2026SOC-ICNN: From Polyhedral to Conic Geometry for Learning Convex Surrogate Functions
608. NeurIPS 2026Soft Forward-Backward Representations for Zero-shot Reinforcement Learning with General Utilities
609. NeurIPS 2026SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning
610. NeurIPS 2026Spatial-IQ: Deconstructing Spatial Intelligence via Hierarchical Capability Tests
611. NeurIPS 2026SpatialFlow-GRPO: Where Spatial Credit Drives Image Editing
612. NeurIPS 2026SPECS: Faster Test-Time Scaling through Speculative Drafts and Dynamic Switching
613. NeurIPS 2026Spectral Geometry of Attention: From Information Routing to Uncertainty
614. NeurIPS 2026Spectral Representations for Provably Robust Offline Meta-Reinforcement Learning from Bagged Rewards
615. NeurIPS 2026Spiking neural network initialization for scale-invariant maximization of entropy
616. NeurIPS 2026Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation
617. NeurIPS 2026Split-RL: Local Conflict Resolution in Reinforcement Learning
618. NeurIPS 2026SPRING: Solver-guided Process Rewards for Novel Logical Reasoning Steps Generation
619. NeurIPS 2026SR-GRPO: Stable Rank as an Intrinsic Geometric Reward for Large Language Model Alignment
620. NeurIPS 2026SRL-MPC: Shape-Aware Reinforcement Learned Model Predictive Control
621. NeurIPS 2026Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR
622. NeurIPS 2026Stabilizing Policy Optimization via Logits Convexity
623. NeurIPS 2026Stable and Granular Policy Optimization for Generative Recommendation
624. NeurIPS 2026StainNFT: Curriculum-Gated Multi-Reward Post-Training for Pathology-Faithful Virtual Staining
625. NeurIPS 2026STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens
626. NeurIPS 2026STARE: Surprisal-Guided Token-Level Advantage Reweighting for Policy Entropy Stability
627. NeurIPS 2026StateTree: Enhancing Long-term Dialogue Reasoning via Reinforcement Learning
628. NeurIPS 2026Statistical Complexity of Soft Bellman Residual Minimization
629. NeurIPS 2026Steer2Edit: From Activation Steering to Component-Level Editing
630. NeurIPS 2026Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces
631. NeurIPS 2026Step-wise Rubric Rewards for LLM Reasoning
632. NeurIPS 2026Stepwise Penalization for Length-Efficient Chain-of-Thought Reasoning
633. NeurIPS 2026StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction
634. NeurIPS 2026Strategic Decision Focused Learning
635. NeurIPS 2026Strengthening LLMs for Tabular Prediction with Structural Priors
636. NeurIPS 2026STRIDE: Learnable Stepwise Language Feedback for LLM Reasoning
637. NeurIPS 2026Structural Entropy Optimized Communication for Multi-Agent Reinforcement Learning
638. NeurIPS 2026Structure-aware Reinforcement Learning for Protein Directed Evolution
639. NeurIPS 2026Subprocess-Constrained Markov Decision Processes
640. NeurIPS 2026Survive or Collapse: The Asymmetric Roles of Data Gating and Reward Grounding in Self-Play RL
641. NeurIPS 2026SWE-Protégé: Learning to Selectively Collaborate With an Expert Unlocks Small Language Models as Software Engineering Agents
642. NeurIPS 2026Synsema: Syntax-Guided Learning of Semantically Valid Programs
643. NeurIPS 2026Tail-Risk-Aware Stackelberg Learning
644. NeurIPS 2026Taming CoT Obfuscation in VLMs: From Mechanistic Evidence to Activation-Level Enforcement
645. NeurIPS 2026Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation
646. NeurIPS 2026TANGO: RNA Topology and Geometry Co-Design
647. NeurIPS 2026TARP: Trace-Anchored Regularization Prior for Retaining Stepwise Reasoning
648. NeurIPS 2026Teach-to-Reason: Competition-Guided Reasoning with a Self-Improving Teacher
649. NeurIPS 2026TEMPO: Temporal Enforcement via Mode-Separated Policy Optimization for Trustworthy LLM Backtesting
650. NeurIPS 2026Temporal Consistency Improves Generalization in Contextual Offline Meta 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.