2 citations · 4 across the 5 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
Neurons in Large Language Models: Dead, N-gram, Positional
Elena Voita, Javier Ferrando, Christoforos Nalmpantis
We analyze a family of large language models in such a lightweight manner that can be done on a single GPU. Specifically, we focus on the OPT family of models ranging from 125m to…
Automating Behavioral Testing in Machine Translation
Javier Ferrando, Matthias Sperber, Hendra Setiawan +2
Behavioral testing in NLP allows fine-grained evaluation of systems by examining their linguistic capabilities through the analysis of input-output behavior. Unfortunately, existin…
Explaining How Transformers Use Context to Build Predictions
Javier Ferrando, Gerard I. Gállego, Ioannis Tsiamas +1
Language Generation Models produce words based on the previous context. Although existing methods offer input attributions as explanations for a model's prediction, it is still unc…