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cs.CL2026

Align, Unify, Suppress, Route: A Coherentist View of Transformer Computation

Nura Aljaafari, Andre Freitas

Mechanistic interpretability has identified transformer circuits, but lacks a shared vocabulary for describing how their functions compose across tasks and architectures. We introd…

cs.CL2026

Principles of Concept Representation in Sentence Encoders

Isabelle Mohr, John Dujany, Jonathan Souquet +1

What makes a sentence encoder produce good concept representations? We approach this through the lens of representational compositionality: an encoder supports a concept family onl…

cs.CL2026

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder

Yingji Zhang, Danilo S. Carvalho, André Freitas

Integrating compositional and symbolic properties into current distributional semantic spaces can enhance the interpretability, controllability, compositionality, and generalisatio…

cs.CL2026

Emergence and Localisation of Semantic Role Circuits in LLMs

Nura Aljaafari, Danilo S. Carvalho, André Freitas

Despite displaying semantic competence, large language models' internal mechanisms that ground abstract semantic structure remain insufficiently characterised. We propose a method…

cs.CL2025

Learning to Disentangle Latent Reasoning Rules with Language VAEs: A Systematic Study

Yingji Zhang, Marco Valentino, Danilo S. Carvalho +1

Incorporating explicit reasoning rules within the latent space of language models (LMs) offers a promising pathway to enhance generalisation, interpretability, and controllability.…

cs.CL2025

TRACE: Training and Inference-Time Interpretability Analysis for Language Models

Nura Aljaafari, Danilo S. Carvalho, André Freitas

Understanding when and how linguistic knowledge emerges during language model training remains a central challenge for interpretability. Most existing tools are post hoc, rely on s…