19 citations · 29 across the 14 of their papers we have counts for
15 papers
SplineWAM: Adaptive Action Horizons for World Action Models via B-Spline Representations
Jun Guo, Xiaoshen Han, Qiwei Li +7
World action models (WAMs) are large embodied policies that jointly predict future video and the actions to execute, emitting a fixed-length action chunk per inference call. Such a…
Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model
Xinghang Li, Jun Guo, Qiwei Li +21
Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements f…
Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation
Nan Sun, Yuan Zhang, Yongkun Yang +10
Embodied chain-of-thought (CoT) aims to bridge linguistic reasoning with robotic control, yet its effective form and integration remain underexplored. In this paper, we revisit emb…
Data Difficulty and the Generalization--Extrapolation Tradeoff in LLM Fine-Tuning
Siyuan Liu, Tinghong Chen, Xinghan Li +2
Data selection during supervised fine-tuning (SFT) can critically change the behavior of large language models (LLMs). Although existing work has studied the effect of selecting da…
RotVLA: Rotational Latent Action for Vision-Language-Action Model
Qiwei Li, Xicheng Gong, Xinghang Li +5
Latent Action Models (LAMs) have emerged as an effective paradigm for handling heterogeneous datasets during Vision-Language-Action (VLA) model pretraining, offering a unified acti…
Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising
Jun Guo, Qiwei Li, Peiyan Li +7
We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruction) in a single framework, a…
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI
Bohan Lyu, Yucheng Yang, Siqiao Huang +25
Modern AI progress has been driven by ML methods that are generalizable across settings and scalable to larger regimes. As large language models demonstrate advanced capabilities i…
SpatialVAM:Spatial-Aware Multi-View Video Diffusion as a Data-Efficient Robot Policy
Peiyan Li, Yixiang Chen, Yuan Xu +13
Robotic manipulation requires understanding both the 3D spatial structure of the environment and its temporal evolution, yet most existing policies neglect one or both aspects. The…
Scaling World Model for Hierarchical Manipulation Policies
Qian Long, Yueze Wang, Jiaxi Song +13
Vision-Language-Action (VLA) models are promising for generalist robot manipulation but remain brittle in out-of-distribution (OOD) settings, especially with limited real-robot dat…
What Matters in Building Vision-Language-Action Models for Generalist Robots
Xinghang Li, Peiyan Li, Long Qian +10
To utilize Foundation Vision Language Models (VLMs) for robotic tasks and motion planning, the community has proposed different methods for injecting action components into VLMs an…
Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
Jialin Zhao, Yingtao Zhang, Xinghang Li +2
The growing demands on GPU memory posed by the increasing number of neural network parameters call for training approaches that are more memory-efficient. Previous memory reduction…
SInViG: A Self-Evolving Interactive Visual Agent for Human-Robot Interaction
Jie Xu, Hanbo Zhang, Xinghang Li +3
Linguistic ambiguity is ubiquitous in our daily lives. Previous works adopted interaction between robots and humans for language disambiguation. Nevertheless, when interactive robo…
Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation
Hongtao Wu, Ya Jing, Chilam Cheang +6
Generative pre-trained models have demonstrated remarkable effectiveness in language and vision domains by learning useful representations. In this paper, we extend the scope of th…
Vision-Language Foundation Models as Effective Robot Imitators
Xinghang Li, Minghuan Liu, Hanbo Zhang +9
Recent progress in vision language foundation models has shown their ability to understand multimodal data and resolve complicated vision language tasks, including robotics manipul…
Mixed Neural Voxels for Fast Multi-view Video Synthesis
Feng Wang, Sinan Tan, Xinghang Li +3
Synthesizing high-fidelity videos from real-world multi-view input is challenging because of the complexities of real-world environments and highly dynamic motions. Previous works…