3 papers
cs.CL2026
When Do Concepts Become Functionally Sufficient During Language-Model Training?
Raphael Bernas, Paul G. Chevalier, Fanny Jourdan +1
Understanding a model and its learning mechanisms in depth requires identifying when its internal structures become useful, rather than simply looking at the final state. We study…
cs.CL2026
Interpreto: An Explainability Library for Transformers
Antonin Poché, Thomas Mullor, Gabriele Sarti +8
Interpreto is an open-source Python library for interpreting HuggingFace language models, from early BERT variants to LLMs. It provides two complementary families of methods: attri…
cs.CL2026
Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics
Raphael Bernas, Fanny Jourdan, Antonin Poché +1
Since their introduction, Transformer architectures have dominated Natural Language Processing (NLP). However, recent research has highlighted an inherent anisotropy phenomenon in…