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Author

Sansheng Cao

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#artificial intelligence Preprint Oct 2026

Looking Inside LLMs: Small-World Connectivity as a Signature of Reasoning Performance

Understanding large language model (LLM) reasoning requires looking beyond behavioral performance to examine how reasoning ability is reflected in internal organization. Inspired by neuroscience findings linking higher intelligence to stronger small-world organization in functional brain networks, we investigate small-...

Zheng Huang, Sansheng Cao, En-Pei Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

$S^3$: Spectral Null-Space Swap Makes Reasoning Models Efficient

This work is the first to unveil the critical role of the null space and harness it for model optimization, and uses a simplified analytical model about optimization to demonstrate why null-space can effectively reduce attention entropy, thereby improving the efficiency of reasoning.

Hong-Bo Ma, Sansheng Cao, Jia-Jun Fan et al. · 0 citations

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