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

911 papers, page 14 of 19

651. ICLR 2026Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models
652. ICLR 2026Reward Is Enough: LLMs Are In-Context Reinforcement Learners
653. ICLR 2026Reward Model Routing in Alignment
654. ICLR 2026RewardEval: Advancing Reward Model Evaluation
655. ICLR 2026Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
656. ICLR 2026RewardMap: Tackling Sparse Rewards in Fine-grained Visual Reasoning via Multi-Stage Reinforcement Learning
657. ICLR 2026RFS: Reinforcement learning with Residual flow steering for dexterous manipulation
658. ICLR 2026RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
659. ICLR 2026Risk-Sensitive Agent Compositions
660. ICLR 2026Risk-Sensitive Reinforcement Learning for Alleviating Exploration Dilemmas in Large Language Models
661. ICLR 2026RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training
662. ICLR 2026RL for Reasoning by Adaptively Revealing Rationales
663. ICLR 2026RL makes MLLMs see better than SFT
664. ICLR 2026RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
665. ICLR 2026RL Squeezes, SFT Expands: A Comparative Study of Reasoning LLMs
666. ICLR 2026RL's Razor: Why Online Reinforcement Learning Forgets Less
667. ICLR 2026RLAP-CLIP: Continual Multimodal Learning with Prototype Adaptation and Difficulty-Aware Routing
668. ICLR 2026RLBFF: Binary Flexible Feedback to bridge between Human Feedback & Verifiable Rewards
669. ICLR 2026RLP: Reinforcement as a Pretraining Objective
670. ICLR 2026RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
671. ICLR 2026RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents
672. ICLR 2026RM-R1: Reward Modeling as Reasoning
673. ICLR 2026Robust Adaptive Multi-Step Predictive Shielding
674. ICLR 2026Robust Decision-Making with Partially Calibrated Forecasters
675. ICLR 2026Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation
676. ICLR 2026Robust Optimization for Mitigating Reward Hacking with Correlated Proxies
677. ICLR 2026Robust Preference Optimization: Aligning Language Models with Noisy Preference Feedback
678. ICLR 2026Robustness in the Face of Partial Identifiability in Reward Learning
679. ICLR 2026ROSETTA: Constructing Code-Based Reward from Unconstrained Language Preference
680. ICLR 2026Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
681. ICLR 2026RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling
682. ICLR 2026SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
683. ICLR 2026SAE as a Crystal Ball: Interpretable Features Predict Cross-domain Transferability of LLMs without Training
684. ICLR 2026Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form
685. ICLR 2026Safe Exploration via Policy Priors
686. ICLR 2026SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety
687. ICLR 2026SafeMPO: Constrained Reinforcement Learning with Probabilistic Incremental Improvement
688. ICLR 2026Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
689. ICLR 2026SAM-Veteran: An MLLM-Based Human-like SAM Agent for Reasoning Segmentation
690. ICLR 2026Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching
691. ICLR 2026Sample Lottery: Unsupervised Discovery of Critical Instances for LLM Reasoning
692. ICLR 2026Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
693. ICLR 2026Sample-efficient and Scalable Exploration in Continuous-Time RL
694. ICLR 2026Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
695. ICLR 2026Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning
696. ICLR 2026Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
697. ICLR 2026Scalable In-Context Q-Learning
698. ICLR 2026Scalable Offline Model-Based RL with Action Chunks
699. ICLR 2026Scaling Agent Learning via Experience Synthesis
700. ICLR 2026Scaling Goal-conditioned Reinforcement Learning with Multistep Quasimetric Distances

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.