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Li Jiang

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Preprint Oct 2026

ContourVLA: A Closed-Loop Perception-Action Contour Policy for Generalized Referring Expression Segmentation

Generalized referring expression segmentation (GRES) requires dynamically balancing high-level semantics for identifying a variable number of language-specified referents with fine-grained visual evidence for precise boundary delineation. This requirement challenges existing cascaded vision-language architectures, whic...

Rui-Cheng Zhang, Kai-Wen Shen, Jia-Qi Hou et al. · 0 citations
Preprint Sep 2026

EVO-WAM: Evolving World Action Models through Video-Action Verification

Improving robot policies on new tasks without collecting additional expert demonstrations remains a central challenge in robot learning. World action models (WAMs) use broad video priors to jointly predict future videos and actions, offering a potential source of supervision for adapting to new tasks. However, generate...

Shi-Long Zhou, Xiong-Hao Wu, Wen-Bo Li et al. · 0 citations
#artificial intelligence Preprint Sep 2026

PrecogUI: Proactive GUI Agents via Pre-cognitive Simulation and Experience Retrieval

Existing reactive Graphical User Interface (GUI) agents often fail in long-horizon, dynamic scenarios, where unexpected disturbances trigger attention-diverting and cascading failures. To address this, we propose PrecogUI, a pre-cognitive architecture that shifts the paradigm from reactive execution to proactive decisi...

Bin Kang, Jia-Rui Ouyang, Li Jiang et al. · 0 citations
Preprint Sep 2026

SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models

SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference, is introduced, providing a reproducible and extensible foundation for interactive world-model research.

Jun-Chao Huang, Guian Fang, Sheng-Ju Qian et al. · 12 citations
Jul 2026

VideoRAE: Taming Video Foundation Models for Generative Modeling via Representation Autoencoders

VideoRAE is introduced, a representation autoencoder that converts features from a frozen video foundation model into compact, reconstruction-capable latents for video generation, establishing frozen video foundation representations as compact, versatile, and generation-friendly video latents.

Zhihao Xie, Junfeng Wu, Xinting Hu et al. · 0 citations

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