activity
20202026
most citedImproving accuracy and speeding up Document Image Classification through parallel systems

32 citations · 62 across the 21 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024★ 1 cited

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

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

Javier Ferrando, Marta R. Costa-jussà

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

cs.CL2024★ 9 cited

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★ 1 cited

Information Flow Routes: Automatically Interpreting Language Models at Scale

Javier Ferrando, Elena Voita

Information flows by routes inside the network via mechanisms implemented in the model. These routes can be represented as graphs where nodes correspond to token representations an…

cs.CL2024★ 2 cited

LM Transparency Tool: Interactive Tool for Analyzing Transformer Language Models

Igor Tufanov, Karen Hambardzumyan, Javier Ferrando +1

We present the LM Transparency Tool (LM-TT), an open-source interactive toolkit for analyzing the internal workings of Transformer-based language models. Differently from previousl…