{"list":"other","total":53,"rows":[{"id":"1607.06450","title":"Layer Normalization","created":"2016-07-21","cited_by_count":5669},{"id":"1801.01290","title":"Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor","created":"2018-01-04","cited_by_count":4885},{"id":"2303.04137","title":"Diffusion Policy: Visuomotor Policy Learning via Action Diffusion","created":"2023-03-07","cited_by_count":2838},{"id":"1802.09477","title":"Addressing Function Approximation Error in Actor-Critic Methods","created":"2018-02-26","cited_by_count":2417},{"id":"2410.24164","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","created":"2024-10-31","cited_by_count":2407},{"id":"2504.16054","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","created":"2025-04-22","cited_by_count":1761},{"id":"2304.13705","title":"Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware","created":"2023-04-23","cited_by_count":1568},{"id":"2503.14734","title":"GR00T N1: An Open Foundation Model for Generalist Humanoid Robots","created":"2025-03-18","cited_by_count":1225},{"id":"2106.06860","title":"A Minimalist Approach to Offline Reinforcement Learning","created":"2021-06-12","cited_by_count":899},{"id":"1910.00177","title":"Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning","created":"2019-10-01","cited_by_count":782},{"id":"2410.07864","title":"RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation","created":"2024-10-10","cited_by_count":691},{"id":"2603.16666","title":"Fast-WAM: Do World Action Models Need Test-time Future Imagination?","created":"2026-03-17","cited_by_count":349},{"id":"2601.21998","title":"Causal World Modeling for Robot Control","created":"2026-01-29","cited_by_count":321},{"id":"2511.14759","title":"$\\pi^{*}_{0.6}$: a VLA That Learns From Experience","created":"2025-11-18","cited_by_count":303},{"id":"2601.16163","title":"Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning","created":"2026-01-22","cited_by_count":300},{"id":"2101.05982","title":"Randomized Ensembled Double Q-Learning: Learning Fast Without a Model","created":"2021-01-15","cited_by_count":288},{"id":"2506.07339","title":"Real-Time Execution of Action Chunking Flow Policies","created":"2025-06-09","cited_by_count":216},{"id":"2410.21845","title":"Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning","created":"2024-10-29","cited_by_count":189},{"id":"2502.02538","title":"Flow Q-Learning","created":"2025-02-04","cited_by_count":184},{"id":"2505.18719","title":"VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning","created":"2025-05-24","cited_by_count":176},{"id":"2506.15799","title":"Steering Your Diffusion Policy with Latent Space Reinforcement Learning","created":"2025-06-18","cited_by_count":169},{"id":"2502.05450","title":"ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy","created":"2025-02-08","cited_by_count":154},{"id":"2509.09674","title":"SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning","created":"2025-09-11","cited_by_count":151},{"id":"2501.16664","title":"Improving Vision-Language-Action Model with Online Reinforcement Learning","created":"2025-01-28","cited_by_count":116},{"id":"2507.07969","title":"Reinforcement Learning with Action Chunking","created":"2025-07-10","cited_by_count":107},{"id":"2410.13816","title":"Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance","created":"2024-10-17","cited_by_count":106},{"id":"2505.22094","title":"ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning","created":"2025-05-28","cited_by_count":97},{"id":"2511.00091","title":"Self-Improving Vision-Language-Action Models with Data Generation via Residual RL","created":"2025-10-30","cited_by_count":78},{"id":"2605.00078","title":"Being-H0.7: A Latent World-Action Model from Egocentric Videos","created":"2026-04-30","cited_by_count":75},{"id":"2512.05964","title":"Training-Time Action Conditioning for Efficient Real-Time Chunking","created":"2025-12-05","cited_by_count":64},{"id":"2510.14830","title":"RL-100: Performant Robotic Manipulation with Real-World Reinforcement Learning","created":"2025-10-16","cited_by_count":59},{"id":"2505.23458","title":"Diffusion Guidance Is a Controllable Policy Improvement Operator","created":"2025-05-29","cited_by_count":58},{"id":"2512.01031","title":"VLASH: Real-Time VLAs via Future-State-Aware Asynchronous Inference","created":"2025-11-30","cited_by_count":58},{"id":"2509.19301","title":"Residual Off-Policy RL for Finetuning Behavior Cloning Policies","created":"2025-09-23","cited_by_count":55},{"id":"2604.23073","title":"RL Token: Bootstrapping Online RL with Vision-Language-Action Models","created":"2026-04-24","cited_by_count":49},{"id":"2509.23224","title":"Leave No Observation Behind: Real-time Correction for VLA Action Chunks","created":"2025-09-27","cited_by_count":46},{"id":"2512.01801","title":"GR-RL: Going Dexterous and Precise for Long-Horizon Robotic Manipulation","created":"2025-12-01","cited_by_count":45},{"id":"2508.02219","title":"CO-RFT: Efficient Fine-Tuning of Vision-Language-Action Models through Chunked Offline Reinforcement Learning","created":"2025-08-04","cited_by_count":37},{"id":"2601.14234","title":"Q-learning with Adjoint Matching","created":"2026-01-20","cited_by_count":37},{"id":"2602.22010","title":"World Guidance: World Modeling in Condition Space for Action Generation","created":"2026-02-25","cited_by_count":36},{"id":"2507.07986","title":"EXPO: Stable Reinforcement Learning with Expressive Policies","created":"2025-07-10","cited_by_count":34},{"id":"2004.06089","title":"Thinking While Moving: Deep Reinforcement Learning with Concurrent Control","created":"2020-04-13","cited_by_count":31},{"id":"2512.10926","title":"Decoupled Q-Chunking","created":"2025-12-11","cited_by_count":20},{"id":"2602.12978","title":"Learning Native Continuation for Action Chunking Flow Policies","created":"2026-02-13","cited_by_count":19},{"id":"2605.00416","title":"Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies","created":"2026-05-01","cited_by_count":15},{"id":"2602.09021","title":"$\\chi_{0}$: Resource-Aware Robust Manipulation via Taming Distributional Inconsistencies","created":"2026-02-09","cited_by_count":12},{"id":"2605.25477","title":"EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models","created":"2026-05-25","cited_by_count":11},{"id":"2512.20188","title":"Asynchronous Fast-Slow Vision-Language-Action Policies for Whole-Body Robotic Manipulation","created":"2025-12-23","cited_by_count":7},{"id":"2603.02083","title":"$\\pi$-StepNFT: Wider Space Needs Finer Steps in Online RL for Flow-based VLAs","created":"2026-03-02","cited_by_count":6},{"id":"2509.25718","title":"VLA Model Post-Training via Action-Chunked PPO and Self Behavior Cloning","created":"2025-09-30","cited_by_count":4},{"id":"2605.08168","title":"Understanding Asynchronous Inference Methods for Vision-Language-Action Models","created":"2026-05-04","cited_by_count":4},{"id":"2603.27450","title":"FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies","created":"2026-03-29","cited_by_count":3},{"id":"2605.25537","title":"Action-Prior Denoising for Smooth Real-Time Chunking","created":"2026-05-25","cited_by_count":1}],"next_cursor":null}