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“VLA” 검색 결과 28건

기술 1

VLA(비전 언어 행동) 모델
AI

뉴스 7

논문 20

From Local Whole-Body VLA Behaviors to Scene-Scale Aerial Manipulation
Multi-Link Safety Filtering for VLA Policies Around Moving Hazards
RawVLA: Embodied Neural Image Signal Processor For Robotic Manipulation
Rho: A Foundation for Efficiently Adaptable VLA Models
Taming VLAs under Robot Execution Errors: Self-Compensation and Stress Testing
Toward Real-Time VLAs: Stage-Aware Two-Step Flow Denoising and System-Level Evaluation
Urgent Actions Go First: Urgency-Aware Denoising for Real-Time VLA Control
When Instructions Retrieve Trajectories: Diagnosing and Mitigating Generalization Failures in VLA Models
Inline Memory Meets Reusable Skills: Memory-centric Framework for Vision-Language-Action Model
Learning from Runtime Feedback through Failure-Bank Self-Evolution for Vision-Language-Action Models
EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action
WayFinder: Hierarchical Visual-Language-Action for Zero-Shot Waypoint Generation and Low-Level Kinematic Control
DynaHarness: A Dynamic Physical Harness for Self-Evolving Robot Agents
Faster and Better? Benchmark Bugs and Design Limitations Distort the Evaluation of Vision-Language-Action Acceleration
MotorMind: Scaffolding General Vision Language Models for Zero-Shot Robot Manipulation
PrefPI: Preference-Guided Steering into Out-of-Distribution Behaviors
ChunkTrust: Adapting Execution Horizons for Robot Policies with Action-Expert Evidence
Tsinghua University, Beijing Academy of Artificial Intelligence (BAAI), Renmin University of China, Shenzhen Technology University, Hefei University of Technology, Jiangnan University, Chongqing University, The Chinese University of Hong Kong
Explore, Execute, Evolve: A Skill Acquisition and Reuse Loop for Embodied Agents
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
π0.5: a Vision-Language-Action Model with Open-World Generalization
Physical Intelligence

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