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Elisa Bassignana

7 accepted papers

2025

The AI Gap: How Socioeconomic Status Affects Language Technology Interactions

ACL 2025long

Socioeconomic status (SES) fundamentally influences how people interact with each other and, more recently, with digital technologies like large language models (LLMs). While previous research has highlighted the interaction between SES and language technology, it was limited by reliance on proxy me…

Cited by 0SourcePDFScholar
2024

Can Humans Identify Domains?

COLING 2024main

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, loosely defined and, in practice, refers to any non-typological property, such as genre, topic, medium or style of a documen…

2024

How to Encode Domain Information in Relation Classification

COLING 2024main

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 obtain better performance is non-trivial. We explore a multi-domain training setup for RC, and attempt to improve performan…

2023

Silver Syntax Pre-training for Cross-Domain Relation Extraction

ACL 2023findings

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 of current RE datasets: obtaining high-quality (manually annotated) data is extremely expensive and cannot realistically…

2022

Evidence > Intuition: Transferability Estimation for Encoder Selection

EMNLP 2022main

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 task a priori—as fine-tuning the entire space of available LMs is computationally prohibitive and unsustainable. However, e…

2022

Experimental Standards for Deep Learning in Natural Language Processing Research

EMNLP 2022finding

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 established disciplines, a lack of common experimental standards remains an open challenge to the field at large. Start…