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Rui-Wu Niu

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Preprint Sep 2026

Network imitation sustains misinformation despite a corrective factual field

Social influence can preserve errors that individuals would correct on their own. We study this possibility by representing opinions as directions in a semantic space. The formulation connects established models of personal preference, social agreement, and external influence. A common factual signal pulls every opinio...

Rui-Wu Niu · 0 citations
#machine learning Preprint Aug 2026

Reciprocity Separates Gradient Flow from Rotation in Conservative Physical Learning

Physical learning lets a trainable material or network use its own physical response to carry error signals, reducing the need for a separately programmed backward computation. We ask what determines whether such a system follows conventional gradient descent or evolves along a genuinely different learning trajectory....

Rui-Wu Niu, Xiao-Wen Bi, M. V. van Wyk · 1 citation
Jul 2026

Reliability-Contagion Feasibility in LLM Multi-Agent Networks

This work forms a correction-aware network model that tracks susceptible, exposed, infectious, and corrected agents and derive its early-invasion condition for heterogeneous communication networks, and couple this propagation model to an analytic majority-vote benchmark in which a clean-task reliability target imposes...

Rui-Wu Niu, Xincheng Shu, Ying Zhao · 0 citations

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