ROBOTNESS
연구

논문

새로 나온 로봇, 피지컬 AI 논문과, 각 논문이 업계에 갖는 의미.

논문 1편
주제전체Manipulation 18VLA 15Navigation 14Perception 9Robotics 9Learning 6Humanoid 5Safety 3Simulation 3Aerial Manipulation 1Co-speech Humanoid 1Distributed Manipulation 1Floorplan SLAM 1Grounding 1Humanoid control 1Locomotion 1Memory-centric VLA 1Model-based RL 1Multi-UAV State Estimation 1Policy 1Real-time VLA 1Safe RL-MPC 1Safe VLA 1Soft Pneumatic Actuators 1Tactile 1Terrain traversability 1Text-to-3D Policy 1Tool Co-Design 1UAV Navigation 1UAV traffic monitoring 1Visual Grounding 1World models 1World-action model 1
난이도전체입문중급전문가
아직 한국어판이 없어 영어 원문으로 표시.
arXiv
Visual Grounding전문가

GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed

Qize Yu, Lianrui Fan, Bowen Ping, Xini Ding, Zetian Song, Junbo Niu, Kaixuan Wang, Tianxing Chen, Yue Chen, Minghua He, Yuran Wang, Jie Huang, Haojun Zhang, Min Chen, Hao Li, Wenxuan Song, Ruihai Wu, Xianming Liu, Shilong Liu, Shuchang Zhou

Preprint. The authors introduce GroundAnything, a 4B-parameter visual grounding model that uses bidirectional diffusion with blockwise denoising for parallel spatial decoding instead of sequential autoregressive token generation. Its autoregressive variant, GroundAnything-VLM, reports 72.42% across 30 grounding benchmarks, ahead of GPT-6 Astra at 71.35%. This matters for latency-sensitive robotics and interactive vision systems that need fast, precise localization.

논문 전문 읽기 (PDF)

논문은 arXiv 로봇 피드에서 가져옵니다. 요약이 아직 작성되지 않은 논문은 초록의 첫 부분을 보여줍니다.