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20242026
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cs.CL2026

Exploring Language-Agnosticity in Function Vectors: A Case Study in Machine Translation

Nurkhan Laiyk, Gerard I. Gállego, Javier Ferrando +1

Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that multilingual model represent…

cs.CL2026

Automated Interpretability and Feature Discovery in Language Models with Agents

Arnau Marin-Llobet, Javier Ferrando

We introduce an autonomous multiagent framework for mechanistic interpretability that automates both explaining and finding internal features in large language models. The system r…

cs.CL2026

Real-Time Detection of Hallucinated Entities in Long-Form Generation

Oscar Obeso, Andy Arditi, Javier Ferrando +3

Large language models are now routinely used in high-stakes applications where hallucinations can cause serious harm, such as medical consultations or legal advice. Existing halluc…

cs.CL2025

Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models

Javier Ferrando, Oscar Obeso, Senthooran Rajamanoharan +1

Hallucinations in large language models are a widespread problem, yet the mechanisms behind whether models will hallucinate are poorly understood, limiting our ability to solve thi…

cs.CL2024

A Primer on the Inner Workings of Transformer-based Language Models

Javier Ferrando, Gabriele Sarti, Arianna Bisazza +1

The rapid progress of research aimed at interpreting the inner workings of advanced language models has highlighted a need for contextualizing the insights gained from years of wor…

cs.CL2024

On the Similarity of Circuits across Languages: a Case Study on the Subject-verb Agreement Task

Javier Ferrando, Marta R. Costa-jussÃ

Several algorithms implemented by language models have recently been successfully reversed-engineered. However, these findings have been concentrated on specific tasks and models,…