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
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
Evaluating twelve open and proprietary models, it is found that abstraction failure is lawful, and the central finding is a gap between recognition and cross-voice mapping: models identify a structure within one voice far better than they carry it across voices; every model pays this tax, and mapping strong enough to n...
Tong Zhang, Zhiyuan Shi, Yun Peng et al.· 0 citations
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