arXiv Machine Learning August 13, 2026 By Kiyotaka Kasubuchi, Kazuo Fukiya

WavePhaseNet: A DFT-Based Method for Constructing Semantic Conceptual Hierarchy Structures (SCHS)

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arXiv:2602. 14419v2 Announce Type: cross Abstract: This paper reformulates Transformer/Attention mechanisms in Large Language Models (LLMs) through measure theory and frequency analysis, theoretically demonstrating that hallucination is an inevitable structural limitation.

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arXiv Machine Learning

Jul 21

The Anatomy of a Truth Direction: Knowledge-Dependent Dimensionality, a Relational Law, and a Convergent Category Geometry in Small Language Models

arXiv:2607. 16741v1 Announce Type: new Abstract: B\"urger et al.

By Francesco Karim Vicidomini

llms

arXiv AI

Jun 3

Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization

arXiv:2606. 03022v1 Announce Type: cross Abstract: Hallucination in Large Language Models (LLMs), characterized by the generation of content inconsistent with contextual facts or logical constraints -- remains a persistent challenge for reliable deployment.

By Mingkuan Zhao, Wentao Hu, Tianchen Huang, Yuheng Min, Suquan Chen, Yide Gao, Yanbo Zhai, Shuangyong Song, Xuelong Li

llms benchmarks safety

arXiv Computation and Language

Aug 24

Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

The paper shows that large language models (LLMs) naturally organize their hidden state manifolds into small‑world networks, enabling efficient multi‑hop reasoning. By converting similarity matrices into unweighted graphs, the authors trace connectivity between distant semantic anchors and find a sharp topological phase transition: deep reasoning layers compress conceptual distances into paths bounded by six semantic hops, while early syntactic layers remain fragmented. The framework is applied to zero‑shot hallucination detection in Retrieval‑Augmented Generation, revealing that factual generations preserve a ~3‑hop structure, whereas hallucinations collapse the topology.

By Md. Faiyaz Abdullah Sayeedi

llms rag safety

arXiv AI

Sep 1

Concepts Whisper: Spectral Anti-Concentration and the Dual Geometry of Transformer Representations

arXiv:2605.01609v2 Announce Type: replace-cross Abstract: We find that transformer concept representations systematically anti-concentrate in the spectral tail of the unembedding covariance, encoding...

By Pratyush Acharya, Nuraj Rimal, Habish Dhakal

llms multimodal safety

arXiv Computation and Language

Aug 25

Bridging Linguistic Structure and Mechanistic Interpretability for Conceptual Interpretation in Language Models

arXiv:2408.11827v2 Announce Type: replace Abstract: Understanding how language models compose meaning from linguistic input remains a central problem in interpretability research. Mechanistic studies...

By Nura Aljaafari, Danilo S. Carvalho, Andr\'e Freitas

llms safety

arXiv Machine Learning

Jul 14

One mechanism for many mental spaces: a shared router over a value slot in language models

arXiv:2607. 10248v1 Announce Type: cross Abstract: Language builds discourse contexts other than the actual: a painting, a belief, a memory, a hypothetical.

By Oliver Steele, Jiangtao Wen, Yuxing Han