4 citations · 4 across the 12 of their papers we have counts for
6 papers · 1 filter
Spatial-Aware VLA Pretraining through Visual-Physical Alignment from Human Videos
Yicheng Feng, Wanpeng Zhang, Ye Wang +4
Vision-Language-Action (VLA) models provide a promising paradigm for robot learning by integrating visual perception with language-guided policy learning. However, most existing ap…
Transport Discrepancy as a Reliability Signal for Vision-Language-Action Models
Wanpeng Zhang, Ye Wang, Hao Luo +6
Vision-language-action (VLA) models that generate continuous action chunks via flow matching lack an internal signal for judging whether a given prediction is reliable. Distributio…
Federated Dialogue-Semantic Diffusion for Emotion Recognition under Incomplete Modalities
Xihang Qiu, Jiarong Cheng, Yuhao Fang +4
Multimodal Emotion Recognition in Conversations (MERC) enhances emotional understanding through the fusion of multimodal signals. However, unpredictable modality absence in real-wo…
Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos
Hao Luo, Yicheng Feng, Wanpeng Zhang +7
We introduce Being-H0, a dexterous Vision-Language-Action model (VLA) trained on large-scale human videos. Existing VLAs struggle with complex manipulation tasks requiring high dex…
Unified Multimodal Understanding via Byte-Pair Visual Encoding
Wanpeng Zhang, Yicheng Feng, Hao Luo +4
Multimodal large language models (MLLMs) have made significant progress in vision-language understanding, yet effectively aligning different modalities remains a fundamental challe…
EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models
Xingrun Xing, Zheng Liu, Shitao Xiao +6
Modern large language models (LLMs) driven by scaling laws, achieve intelligence emergency in large model sizes. Recently, the increasing concerns about cloud costs, latency, and p…