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Qi Lv

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO2
  • cs.CV1
  • cs.LG1
same name
  • Qi Lv — 3 papers
  • Qi Lv — 2 papers, h 14
  • Qi Lv — 2 papers
  • Qi Lv — 1 paper
  • Qi Lv — 1 paper
  • Qi Lv — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedAdaptive Sparse Softmax: An Effective and Efficient Softmax Variant

3 citations · 3 across the 2 of their papers we have counts for

collaborators

4 papers

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

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.