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Showing papers from Shanghai JiaoTong Unversity Show all papers

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NeurIPS 2026Shanghai JiaoTong UnversityShanghai Jiao TongShanghai JiaotongVision-language models

GIVLA: Deep Geometry Internalization for A Lightweight VLA via Geometry Instruction and Gradient-Informed Training

YUNHE LI, Qiming Liu, Haoyuan Wang, Hesheng Wang

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai JiaotongBeijing Academy of Artificial InTongjiShanghai JiaoTong UnversityInstitute for Computer Science, Vision-language-action models

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

Evo-Depth is a lightweight 0.9-billion-parameter vision-language-action model using implicit depth encoding from RGB to improve spatial manipulation without extra sensors. It achieves top benchmark performance with minimal GPU memory and highest inference speed among compared methods.

Tao Lin, Yuxin Du, Jiting Liu, Nuobei Zhu and 13 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5