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Yuze Wu

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#machine learning Preprint Sep 2026

Revisiting On-policy Adversarial Black-Box Distillation: Calibrating Groupwise Reward Geometry for Effective Advantage Construction

Black-box distillation is a practical route for transferring capabilities from API-accessible large language models that expose only text outputs into smaller student models. Recent on-policy adversarial methods such as GAD improve over SeqKD by forming an adversarial loop between a critic and a student, where the crit...

Xiao Cui, Mo Zhu, Yu-Lei Qin et al. · 1 citation
#artificial intelligence Preprint Sep 2026

DiffWAM: A Fast and Efficient Navigation World Action Model

Pretrained video foundation models encode rich semantic and spatiotemporal priors for embodied navigation, yet converting these priors into UAV motion typically requires expensive future-video synthesis and geometric reconstruction. We investigate whether the motion implicit in future visual prediction can instead be r...

Morui Zhu, Yu-Ze Wu, Xi-Jie Huang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

NavGen: Visual Generative Models as a Scalable Data Engine for Embodied 3D Navigation

NavGen is introduced, a text-to-video data generation pipeline that produces diverse vision-language navigation episodes across indoor and outdoor scenes and a style-diversification method that scales up long-tail data that is difficult and costly to collect.

Xi-Jie Huang, Yong-Yang Wan, Cheng-Bin Dong et al. · 0 citations
Jul 2026

D-VLC: Decentralized Vision-Language Collaboration for Heterogeneous Embodied Multi-Robot Systems in Unknown Environments

A framework that combines decentralized asynchronous reasoning, lightweight information sharing, capability aware collaboration, and a unified action interface is proposed, enabling general purpose VLMs to generate robot specific actions executed by learning free experts without task or robot specific training.

Yuan Zhou, Ruitong Lin, Shen Wang et al. · 1 citation

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