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Weiliang Chen

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#machine learning Preprint Oct 2026

S-Space: Exploring Spatial Workspace in Multimodal Language Models

Multimodal language models (MLLMs) exhibit promising spatial reasoning capabilities, yet the internal mechanisms supporting them remain poorly understood. We uncover S-Space, a linear representation subspace in which object-token representations encode continuous coordinates along horizontal, vertical, and distance axe...

Zhi-Yuan Shi, Xiang Li, Xing-Zhuo Guo et al. · 0 citations
Preprint Aug 2026

HarnessEval-W: Agentifying the Evaluation of Visual Worlds

A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially critical for world models, where judging a rollout requires understanding whether physics, causality, and world state evolve correctly. Humans spot such violations natu...

Weiliang Chen, Haowen Sun, Jun Gao et al. · 2 citations
Preprint Aug 2026

Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning

Experiments show that Code-as-World-VL achieves state-of-the-art performance on QuantiPhy and surpasses leading proprietary models, highlighting the potential of executable world representations as a scalable foundation for physical intelligence.

Han-Yang Wang, Yiyang Cai, Wei-Liang Chen et al. · 10 citations · ⚡1

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