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20222026
most citedGeneral and Domain Adaptive Chinese Spelling Check with Error Consistent Pretraining

27 citations · 32 across the 15 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.RO2025

F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions

Qi Lv, Weijie Kong, Hao Li +7

Executing language-conditioned tasks in dynamic visual environments remains a central challenge in embodied AI. Existing Vision-Language-Action (VLA) models predominantly adopt rea…

cs.LG2025★ 3 cited

Adaptive Sparse Softmax: An Effective and Efficient Softmax Variant

Qi Lv, Lei Geng, Ziqiang Cao +4

Softmax with the cross entropy loss is the standard configuration for current neural classification models. The gold score for a target class is supposed to be 1, but it is never r…

cs.RO2025

EO-1: An Open Unified Embodied Foundation Model for General Robot Control

Delin Qu, Haoming Song, Qizhi Chen +13

The human ability to seamlessly perform multimodal reasoning and physical interaction in the open world is a core goal for general purpose embodied intelligent systems. Recent visi…

cs.RO2025

STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization

Hao Li, Qi Lv, Rui Shao +4

Transforming complex actions into discrete skill abstractions has demonstrated strong potential for robotic manipulation. Existing approaches mainly leverage latent variable models…

cs.RO2025

Spatial-Temporal Graph Diffusion Policy with Kinematic Modeling for Bimanual Robotic Manipulation

Qi Lv, Hao Li, Xiang Deng +6

Despite the significant success of imitation learning in robotic manipulation, its application to bimanual tasks remains highly challenging. Existing approaches mainly learn a poli…

cs.CV2025

3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds

Hengshuo Chu, Xiang Deng, Qi Lv +4

3D Affordance detection is a challenging problem with broad applications on various robotic tasks. Existing methods typically formulate the detection paradigm as a label-based sema…