{"total":20,"rows":[{"id":"2511.14759","title":"$\\pi^{*}_{0.6}$: a VLA That Learns From Experience","created":"2025-11-18","cited_by_count":303,"area":"vla"},{"id":"2604.23073","title":"RL Token: Bootstrapping Online RL with Vision-Language-Action Models","created":"2026-04-24","cited_by_count":49,"area":"vla"},{"id":"2601.03044","title":"SOP: A Scalable Online Post-Training System for Vision-Language-Action Models","created":"2026-01-06","cited_by_count":21,"area":"vla"},{"id":"2605.00416","title":"Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies","created":"2026-05-01","cited_by_count":15,"area":"vla"},{"id":"2605.25477","title":"EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models","created":"2026-05-25","cited_by_count":11,"area":"vla"},{"id":"2606.23686","title":"LIBERO-Safety: A Comprehensive Benchmark for Physical and Semantic Safety in Vision-Language-Action Models","created":"2026-06-22","cited_by_count":10,"area":"vla"},{"id":"2510.17640","title":"RESample: A Robust Data Augmentation Framework via Exploratory Sampling for Robotic Manipulation","created":"2025-10-20","cited_by_count":6,"area":"vla"},{"id":"2602.09023","title":"TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation","created":"2026-02-09","cited_by_count":6,"area":"vla"},{"id":"2606.09337","title":"TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation","created":"2026-06-08","cited_by_count":4,"area":"vla"},{"id":"2607.27782","title":"RedFlow: Redirect Failure into Action-Level Corrections for Flow-matching VLA Policy","created":"2026-07-30","cited_by_count":4,"area":"vla"},{"id":"2606.10305","title":"SARM2: Multi-Task Stage Aware Reward Modeling for Self Improving Robotic Manipulation","created":"2026-06-09","cited_by_count":2,"area":"vla"},{"id":"2606.26006","title":"FORCE: Efficient VLA Reinforcement Fine-Tuning via Value-Calibrated Warm-up and Self-Distillation","created":"2026-06-24","cited_by_count":2,"area":"vla"},{"id":"2609.18207","title":"Reinforcement Learning for Real-Time Vision-Language-Action Policies","created":"2026-09-16","cited_by_count":2,"area":"vla"},{"id":"2605.30226","title":"BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models","created":"2026-05-28","cited_by_count":1,"area":"vla"},{"id":"2606.04968","title":"Potential-Guided Flow Matching for Vision-Language-Action Policy Improvement","created":"2026-06-03","cited_by_count":1,"area":"vla"},{"id":"2606.22860","title":"HiL-ResRL: A Model-Agnostic Finetuning Adapter via Human-in-the-loop Residual Reinforcement Learning","created":"2026-06-22","cited_by_count":1,"area":"vla"},{"id":"2608.16837","title":"HAF: Adapting Generalist VLAs to Humanoid Whole-Body Loco-manipulation via Hierarchical Action Flow and Spectral Latent RL","created":"2026-08-17","cited_by_count":1,"area":"vla"},{"id":"2606.09009","title":"Scaling by Diversified Experience for Vision-Language-Action Models","created":"2026-06-08","cited_by_count":0,"area":"vla"},{"id":"2606.17011","title":"ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning","created":"2026-06-15","cited_by_count":0,"area":"vla"},{"id":"2609.27450","title":"BEE: Intervention-Adaptive Real-World Reinforcement Learning with Vision-Language-Action Models","created":"2026-09-23","cited_by_count":0,"area":"vla"}],"next_cursor":null}