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Unsupervised Discovery of Language and Topic Lanes in Transformer Models via Multilingual Co-firing Signatures

Chen, Ho Yiing · 2026-05-21 · Zenodo

doi:10.5281/zenodo.20313748 · PDF

Abstract

I run ten multilingual prompts through qwen2.5:7B while recording per-prompt activation at every sensor in a one-million-cell Mercury grid. The output is a binary signature for each active cell, encoding which prompts triggered it. From 14,912 active cells, 944 distinct firing patterns appear. Categorizing cells by signature recovers six functional 'lanes' with no supervised labels: a universal backbone (39 cells fire in all ten queries), a Chinese-only language detector (73 cells), an English-only language detector (56 cells), and three topic lanes. The headline result is a cross-language phy

Chen, Ho Yiing (norika) · Independent Researcher, Taiwan · ORCID 0009-0006-6816-9891