Contrastive-Difference CKA Reveals Concept-Specific Structural Alignment Across Language Model Architectures 文章

ArXiv CS.CL2026-06-16NEWSen作者: Xueping Gao

详细信息

来源站点
ArXiv CS.CL
作者
Xueping Gao
文章类型
NEWS
语言
en
发布日期
2026-06-16

摘要

arXiv:2606.16897v1 Announce Type: new Abstract: Do different LLM architectures encode high-level concepts in structurally compatible ways? We systematically characterize a geometric-functional universality dissociation: across multiple concept domains and architectural families, moderate geometric convergence coexists with near-perfect functional transfer. Using contrastive-difference CKA (CKA_Delta), a training-free diagnostic that computes kernel alignment on per-sample contrastive differences, we isolate concept-specific convergence from generic similarity -- achieving significant discrimination where standard CKA cannot. The dissociation replicates across all six concept domains we test (five with p =70B models. We position CKA_Delta as a practical regime classifier and architectural outlier detector (Gemma: d = 1.08, AUC = 0.79) rather than an absolute transfer-accuracy predictor, providing a training-free diagnostic for cross-architecture concept monitoring.

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