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 20 of 138

951. ICLR 2026RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
952. ICLR 2026Risk-Sensitive Agent Compositions
953. ICLR 2026Risk-Sensitive Reinforcement Learning for Alleviating Exploration Dilemmas in Large Language Models
954. ICLR 2026RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training
955. ICLR 2026RL for Reasoning by Adaptively Revealing Rationales
956. ICLR 2026RL makes MLLMs see better than SFT
957. ICLR 2026RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
958. ICLR 2026RL Squeezes, SFT Expands: A Comparative Study of Reasoning LLMs
959. ICLR 2026RL's Razor: Why Online Reinforcement Learning Forgets Less
960. ICLR 2026RLAP-CLIP: Continual Multimodal Learning with Prototype Adaptation and Difficulty-Aware Routing
961. ICLR 2026RLBFF: Binary Flexible Feedback to bridge between Human Feedback & Verifiable Rewards
962. ICLR 2026RLP: Reinforcement as a Pretraining Objective
963. ICLR 2026RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
964. ICLR 2026RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents
965. ICLR 2026RM-R1: Reward Modeling as Reasoning
966. ICLR 2026Robust Adaptive Multi-Step Predictive Shielding
967. ICLR 2026Robust Decision-Making with Partially Calibrated Forecasters
968. ICLR 2026Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation
969. ICLR 2026Robust Optimization for Mitigating Reward Hacking with Correlated Proxies
970. ICLR 2026Robust Preference Optimization: Aligning Language Models with Noisy Preference Feedback
971. ICLR 2026Robustness in the Face of Partial Identifiability in Reward Learning
972. ICLR 2026ROSETTA: Constructing Code-Based Reward from Unconstrained Language Preference
973. ICLR 2026Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
974. ICLR 2026RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling
975. ICLR 2026SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
976. ICLR 2026SAE as a Crystal Ball: Interpretable Features Predict Cross-domain Transferability of LLMs without Training
977. ICLR 2026Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form
978. ICLR 2026Safe Exploration via Policy Priors
979. ICLR 2026SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety
980. ICLR 2026SafeMPO: Constrained Reinforcement Learning with Probabilistic Incremental Improvement
981. ICLR 2026Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
982. ICLR 2026SAM-Veteran: An MLLM-Based Human-like SAM Agent for Reasoning Segmentation
983. ICLR 2026Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching
984. ICLR 2026Sample Lottery: Unsupervised Discovery of Critical Instances for LLM Reasoning
985. ICLR 2026Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
986. ICLR 2026Sample-efficient and Scalable Exploration in Continuous-Time RL
987. ICLR 2026Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
988. ICLR 2026Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning
989. ICLR 2026Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
990. ICLR 2026Scalable In-Context Q-Learning
991. ICLR 2026Scalable Offline Model-Based RL with Action Chunks
992. ICLR 2026Scaling Agent Learning via Experience Synthesis
993. ICLR 2026Scaling Goal-conditioned Reinforcement Learning with Multistep Quasimetric Distances
994. ICLR 2026Scaling Linear Attention with Sparse State Expansion
995. ICLR 2026Scaling Synthetic Task Generation for Agents via Exploration
996. ICLR 2026Scheduling Your LLM Reinforcement Learning with Reasoning Trees
997. ICLR 2026SCOPED: Score–Curvature Out-of-distribution Proximity Evaluator for Diffusion
998. ICLR 2026SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning
999. ICLR 2026Sculptor: Empowering LLMs with Cognitive Agency via Active Context Management
1000. ICLR 2026Search Self-Play: Pushing the Frontier of Agent Capability without Supervision

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.