3 citations · 11 across the 10 of their papers we have counts for
11 papers
The AI Gap: How Socioeconomic Status Affects Language Technology Interactions
Elisa Bassignana, Amanda Cercas Curry, Dirk Hovy
Socioeconomic status (SES) fundamentally influences how people interact with each other and more recently, with digital technologies like Large Language Models (LLMs). While previo…
How to Encode Domain Information in Relation Classification
Elisa Bassignana, Viggo Unmack Gascou, Frida Nøhr Laustsen +4
Current language models require a lot of training data to obtain high performance. For Relation Classification (RC), many datasets are domain-specific, so combining datasets to obt…
Can Humans Identify Domains?
Maria Barrett, Max Müller-Eberstein, Elisa Bassignana +3
Textual domain is a crucial property within the Natural Language Processing (NLP) community due to its effects on downstream model performance. The concept itself is, however, loos…
Silver Syntax Pre-training for Cross-Domain Relation Extraction
Elisa Bassignana, Filip Ginter, Sampo Pyysalo +2
Relation Extraction (RE) remains a challenging task, especially when considering realistic out-of-domain evaluations. One of the main reasons for this is the limited training size…
Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction
Elisa Bassignana, Filip Ginter, Sampo Pyysalo +2
Most research in Relation Extraction (RE) involves the English language, mainly due to the lack of multi-lingual resources. We propose Multi-CrossRE, the broadest multi-lingual dat…
Evidence > Intuition: Transferability Estimation for Encoder Selection
Elisa Bassignana, Max Müller-Eberstein, Mike Zhang +1
With the increase in availability of large pre-trained language models (LMs) in Natural Language Processing (NLP), it becomes critical to assess their fit for a specific target tas…
CrossRE: A Cross-Domain Dataset for Relation Extraction
Elisa Bassignana, Barbara Plank
Relation Extraction (RE) has attracted increasing attention, but current RE evaluation is limited to in-domain evaluation setups. Little is known on how well a RE system fares in c…
What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification
Elisa Bassignana, Barbara Plank
Over the last five years, research on Relation Extraction (RE) witnessed extensive progress with many new dataset releases. At the same time, setup clarity has decreased, contribut…
Experimental Standards for Deep Learning in Natural Language Processing Research
Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein +5
The field of Deep Learning (DL) has undergone explosive growth during the last decade, with a substantial impact on Natural Language Processing (NLP) as well. Yet, compared to more…
Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality
Elisa Bassignana, Malvina Nissim, Viviana Patti
As a contribution to personality detection in languages other than English, we rely on distant supervision to create Personal-ITY, a novel corpus of YouTube comments in Italian, wh…
Personal-ITY: A Novel YouTube-based Corpus for Personality Prediction in Italian
Elisa Bassignana, Malvina Nissim, Viviana Patti
We present a novel corpus for personality prediction in Italian, containing a larger number of authors and a different genre compared to previously available resources. The corpus…