SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 15113 papers

TitleStatusHype
The Hallucination Dilemma: Factuality-Aware Reinforcement Learning for Large Reasoning ModelsCode1
ROAD: Responsibility-Oriented Reward Design for Reinforcement Learning in Autonomous Driving—0
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language ModelsCode5
Contextual Integrity in LLMs via Reasoning and Reinforcement Learning—0
Reinforcement Learning for Better Verbalized Confidence in Long-Form Generation—0
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning—0
Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning—0
Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language ModelsCode1
Fortune: Formula-Driven Reinforcement Learning for Symbolic Table Reasoning in Language Models—0
Hybrid Cross-domain Robust Reinforcement Learning—0
Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data—0
Diversity-Aware Policy Optimization for Large Language Model Reasoning—0
Normalizing Flows are Capable Models for RLCode1
Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability—0
Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners—0
Jigsaw-R1: A Study of Rule-based Visual Reinforcement Learning with Jigsaw PuzzlesCode1
LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Trainin—0
Grounded Reinforcement Learning for Visual ReasoningCode0
ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning EngineeringCode2
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization—0
Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software EngineeringCode1
Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control—0
Fine-Tuning Next-Scale Visual Autoregressive Models with Group Relative Policy Optimization—0
DIP-R1: Deep Inspection and Perception with RL Looking Through and Understanding Complex Scenes—0
Unsupervised Transcript-assisted Video Summarization and Highlight Detection—0
SOReL and TOReL: Two Methods for Fully Offline Reinforcement LearningCode0
Advancing Multimodal Reasoning via Reinforcement Learning with Cold StartCode1
Maximizing Confidence Alone Improves Reasoning—0
Decomposing Elements of Problem Solving: What "Math" Does RL Teach?Code0
Scaling Offline RL via Efficient and Expressive Shortcut Models—0
When Does Neuroevolution Outcompete Reinforcement Learning in Transfer Learning Tasks?Code0
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning—0
Enhancing Study-Level Inference from Clinical Trial Papers via RL-based Numeric Reasoning—0
Skywork Open Reasoner 1 Technical ReportCode4
Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPOCode2
cadrille: Multi-modal CAD Reconstruction with Online Reinforcement LearningCode2
Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean-Field Games—0
ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning—0
A Provable Approach for End-to-End Safe Reinforcement Learning—0
FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control—0
HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI GymCode0
MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment GroundingCode1
Rendering-Aware Reinforcement Learning for Vector Graphics Generation—0
Reinforcing General Reasoning without VerifiersCode2
SPA-RL: Reinforcing LLM Agents via Stepwise Progress AttributionCode2
Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning—0
R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement LearningCode1
Interactive OT Gym: A Reinforcement Learning-Based Interactive Optical tweezer (OT)-Driven Microrobotics Simulation Platform—0
Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies—0
Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RLCode1
Show:102550
← PrevPage 5 of 303Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified