{"total":32,"rows":[{"id":"2507.15597","title":"Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos","created":"2025-07-21","cited_by_count":102,"area":"vla"},{"id":"2601.12993","title":"Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization","created":"2026-01-19","cited_by_count":66,"area":"vla"},{"id":"2508.13446","title":"CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models","created":"2025-08-19","cited_by_count":29,"area":"vla"},{"id":"2511.15605","title":"SRPO: Self-Referential Policy Optimization for Vision-Language-Action Models","created":"2025-11-19","cited_by_count":27,"area":"vla"},{"id":"2509.15212","title":"RynnVLA-001: Using Human Demonstrations to Improve Robot Manipulation","created":"2025-09-18","cited_by_count":25,"area":"vla"},{"id":"2601.09708","title":"Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning","created":"2026-01-14","cited_by_count":24,"area":"vla"},{"id":"2602.01067","title":"A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation","created":"2026-02-01","cited_by_count":22,"area":"vla"},{"id":"2511.17889","title":"MobileVLA-R1: Reinforcing Vision-Language-Action for Mobile Robots","created":"2025-11-22","cited_by_count":15,"area":"vla"},{"id":"2512.02787","title":"Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols","created":"2025-12-02","cited_by_count":14,"area":"vla"},{"id":"2512.13080","title":"Spatial-Aware VLA Pretraining through Visual-Physical Alignment from Human Videos","created":"2025-12-15","cited_by_count":13,"area":"vla"},{"id":"2606.10267","title":"What Matters in Orchestrating Robot Policies: A Systematic Study of Hierarchical VLA Agents","created":"2026-06-09","cited_by_count":11,"area":"vla"},{"id":"2604.08168","title":"ViVa: A Video-Generative Value Model for Robot Reinforcement Learning","created":"2026-04-09","cited_by_count":9,"area":"vla"},{"id":"2602.12322","title":"ForeAct: Steering Your VLA with Efficient Visual Foresight Planning","created":"2026-02-12","cited_by_count":8,"area":"vla"},{"id":"2603.12193","title":"SaPaVe: Towards Active Perception and Manipulation in Vision-Language-Action Models for Robotics","created":"2026-03-12","cited_by_count":8,"area":"vla"},{"id":"2602.09722","title":"Rethinking Visual-Language-Action Model Scaling: Alignment, Mixture, and Regularization","created":"2026-02-10","cited_by_count":7,"area":"vla"},{"id":"2602.19710","title":"PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies","created":"2026-02-23","cited_by_count":7,"area":"vla"},{"id":"2603.10052","title":"OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies","created":"2026-03-09","cited_by_count":6,"area":"vla"},{"id":"2605.18287","title":"StableVLA: Towards Robust Vision-Language-Action Models without Extra Data","created":"2026-05-18","cited_by_count":4,"area":"vla"},{"id":"2605.24642","title":"Understanding the Impact of Geometric Foundation Models on Vision-Language-Action Models","created":"2026-05-23","cited_by_count":4,"area":"vla"},{"id":"2606.18247","title":"Visual Verification Enables Inference-time Steering and Autonomous Policy Improvement","created":"2026-06-16","cited_by_count":3,"area":"vla"},{"id":"2510.10642","title":"UniJEPA: Enhancing Robot Policy via Unified Continuous and Discrete Representation Learning","created":"2025-10-12","cited_by_count":2,"area":"vla"},{"id":"2512.03913","title":"Hierarchical Vision Language Action Model Using Success and Failure Demonstrations","created":"2025-12-03","cited_by_count":2,"area":"vla"},{"id":"2604.18000","title":"Unmasking the Illusion of Embodied Reasoning in Vision-Language-Action Models","created":"2026-04-20","cited_by_count":2,"area":"vla"},{"id":"2607.02841","title":"CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving","created":"2026-07-03","cited_by_count":2,"area":"vla"},{"id":"2607.18231","title":"FM-VLA: Force-based Memory for Vision-Language-Action Models in Contact-Rich Manipulation","created":"2026-07-20","cited_by_count":2,"area":"vla"},{"id":"2604.21232","title":"ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures","created":"2026-04-23","cited_by_count":1,"area":"vla"},{"id":"2606.00985","title":"Make Your VLA More Robust Without More Data By Interleaving Motion Planning","created":"2026-05-31","cited_by_count":1,"area":"vla"},{"id":"2609.06251","title":"MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control","created":"2026-09-05","cited_by_count":1,"area":"vla"},{"id":"2606.04046","title":"Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation","created":"2026-06-02","cited_by_count":0,"area":"vla"},{"id":"2606.24049","title":"SPACE: Enabling Learning from Cross-Robot Data Toward Generalist Policies","created":"2026-06-23","cited_by_count":0,"area":"vla"},{"id":"2610.00899","title":"TOAST: Stochastic Robot Action Tokenization for Autoregressive Vision-Language-Action Models","created":"2026-10-01","cited_by_count":0,"area":"vla"},{"id":"2610.01741","title":"ATI-VLA: Action-Centric Predictive Vision-Language-Action Models via Actionable Alignment Then Adaptive Injection","created":"2026-10-01","cited_by_count":0,"area":"vla"}],"next_cursor":null}