1 citations · 2 across the 8 of their papers we have counts for
10 papers
What Matters in Quality-Aware VLA Pretraining: A Benchmark and Empirical Study
Mingxuan Yan, Litian Gong, Dihong Huang +19
How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning? We compare weighting, filtering, and…
Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation
Xincheng He, Siyu Ma, Chang Yu +5
Transferring robotic skills from simulation to reality requires task knowledge that remains usable across differences in perception, dynamics, and embodiment. We introduce Skill2Re…
AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation
Mengfei Zhao, Dihong Huang, Yikai Tang +12
Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on speciali…
Fishbone: From One 3D Asset to a Million Controllable Edits
Yumeng He, Xiaoying Wang, Peihao Li +7
Large-scale controllable 3D assets are critical for computer graphics, embodied AI, robotics, and interactive content creation, yet creating diverse 3D assets remains challenging d…
VISTAv2: World Imagination for Indoor Vision-and-Language Navigation
Yanjia Huang, Xianshun Jiang, Xiangbo Gao +2
Vision-and-Language Navigation (VLN) requires agents to follow language instructions while acting in continuous real-world spaces. Prior image imagination based VLN work shows bene…
FORGE-Tree: Diffusion-Forcing Tree Search for Long-Horizon Robot Manipulation
Yanjia Huang, Shuo Liu, Sheng Liu +4
Long-horizon robot manipulation tasks remain challenging for Vision-Language-Action (VLA) policies due to drift and exposure bias, often denoise the entire trajectory with fixed hy…
VISTA: Generative Visual Imagination for Vision-and-Language Navigation
Yanjia Huang, Mingyang Wu, Renjie Li +1
Vision-and-Language Navigation (VLN) tasks agents with locating specific objects in unseen environments using natural language instructions and visual cues. Many existing VLN appro…
Can Large Vision Language Models Read Maps Like a Human?
Shuo Xing, Zezhou Sun, Shuangyu Xie +6
In this paper, we introduce MapBench-the first dataset specifically designed for human-readable, pixel-based map-based outdoor navigation, curated from complex path finding scenari…
PANDORA: Diffusion Policy Learning for Dexterous Robotic Piano Playing
Yanjia Huang, Renjie Li, Zhengzhong Tu
We present PANDORA, a novel diffusion-based policy learning framework designed specifically for dexterous robotic piano performance. Our approach employs a conditional U-Net archit…
Zero-shot Object Navigation with Vision-Language Models Reasoning
Congcong Wen, Yisiyuan Huang, Hao Huang +6
Object navigation is crucial for robots, but traditional methods require substantial training data and cannot be generalized to unknown environments. Zero-shot object navigation (Z…