7 citations · 10 across the 3 of their papers we have counts for
3 papers
Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference
Jorge García-Carrasco, Alejandro Maté, Juan Trujillo
Large Language Models (LLMs) have shown impressive performance across a wide range of tasks. However, the size of LLMs is steadily increasing, hindering their application on comput…
Detecting and Understanding Vulnerabilities in Language Models via Mechanistic Interpretability
Jorge García-Carrasco, Alejandro Maté, Juan Trujillo
Large Language Models (LLMs), characterized by being trained on broad amounts of data in a self-supervised manner, have shown impressive performance across a wide range of tasks. I…
How does GPT-2 Predict Acronyms? Extracting and Understanding a Circuit via Mechanistic Interpretability
Jorge García-Carrasco, Alejandro Maté, Juan Trujillo
Transformer-based language models are treated as black-boxes because of their large number of parameters and complex internal interactions, which is a serious safety concern. Mecha…