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

784 papers, page 15 of 16

701. NeurIPS 2025Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies
702. NeurIPS 2025Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling
703. NeurIPS 2025Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds
704. NeurIPS 2025Towards Principled Unsupervised Multi-Agent Reinforcement Learning
705. NeurIPS 2025Towards Provable Emergence of In-Context Reinforcement Learning
706. NeurIPS 2025Towards Reliable Code-as-Policies: A Neuro-Symbolic Framework for Embodied Task Planning
707. NeurIPS 2025Towards Robust Zero-Shot Reinforcement Learning
708. NeurIPS 2025Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization
709. NeurIPS 2025TP-MDDN: Task-Preferenced Multi-Demand-Driven Navigation with Autonomous Decision-Making
710. NeurIPS 2025Tracing the Representation Geometry of Language Models from Pretraining to Post-training
711. NeurIPS 2025Train on Pins and Test on Obstacles for Rectilinear Steiner Minimum Tree
712. NeurIPS 2025Training a Scientific Reasoning Model for Chemistry
713. NeurIPS 2025Training Language Models to Generate Quality Code with Program Analysis Feedback
714. NeurIPS 2025Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training
715. NeurIPS 2025Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning
716. NeurIPS 2025Trajectory Graph Learning: Aligning with Long Trajectories in Reinforcement Learning Without Reward Design
717. NeurIPS 2025Tree-Guided Diffusion Planner
718. NeurIPS 2025Tru-POMDP: Task Planning Under Uncertainty via Tree of Hypotheses and Open-Ended POMDPs
719. NeurIPS 2025Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm
720. NeurIPS 2025Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
721. NeurIPS 2025TTRL: Test-Time Reinforcement Learning
722. NeurIPS 2025Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound
723. NeurIPS 2025UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection
724. NeurIPS 2025UFT: Unifying Supervised and Reinforcement Fine-Tuning
725. NeurIPS 2025Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design
726. NeurIPS 2025Uncertainty-aware Preference Alignment for Diffusion Policies
727. NeurIPS 2025Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations
728. NeurIPS 2025Uncertainty-Guided Exploration for Efficient AlphaZero Training
729. NeurIPS 2025Uncertainty-quantified Rollout Policy Adaptation for Unlabelled Cross-domain Video Temporal Grounding
730. NeurIPS 2025Uncertainty-Sensitive Privileged Learning
731. NeurIPS 2025Understanding Data Influence in Reinforcement Finetuning
732. NeurIPS 2025Uni-RL: Unifying Online and Offline RL via Implicit Value Regularization
733. NeurIPS 2025UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning
734. NeurIPS 2025Unified Reinforcement and Imitation Learning for Vision-Language Models
735. NeurIPS 2025UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems
736. NeurIPS 2025Unlocking Multimodal Mathematical Reasoning via Process Reward Model
737. NeurIPS 2025Unveiling Chain of Step Reasoning for Vision-Language Models with Fine-grained Rewards
738. NeurIPS 2025Unveiling the Compositional Ability Gap in Vision-Language Reasoning Model
739. NeurIPS 2025URB - Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles
740. NeurIPS 2025Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought
741. NeurIPS 2025Value Diffusion Reinforcement Learning
742. NeurIPS 2025Value Gradient Guidance for Flow Matching Alignment
743. NeurIPS 2025Value Improved Actor Critic Algorithms
744. NeurIPS 2025Value-Guided Decision Transformer: A Unified Reinforcement Learning Framework for Online and Offline Settings
745. NeurIPS 2025Value-Guided Search for Efficient Chain-of-Thought Reasoning
746. NeurIPS 2025VaporTok: RL-Driven Adaptive Video Tokenizer with Prior & Task Awareness
747. NeurIPS 2025VERA: Variational Inference Framework for Jailbreaking Large Language Models
748. NeurIPS 2025ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs
749. NeurIPS 2025VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation Models
750. NeurIPS 2025Video-R1: Reinforcing Video Reasoning in MLLMs

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.