Elisa Bassignana

Elisa Bassignana

Postdoctoral researcher in NLP

Publications

Cross-domain Relation Extraction

Elisa Bassignana
PhD thesis, IT University of Copenhagen

Thesis Slides

Dissecting Biases in Relation Extraction: A Cross-Dataset Analysis on People’s Gender and Origin

Marco Antonio Stranisci*, Pere-Lluís Huguet Cabot*, Elisa Bassignana*, Roberto Navigli
In Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP 2024)
(*): equal contribution

Paper Poster

What's wrong with your model? A Quantitative Analysis of Relation Classification

Elisa Bassignana, Rob van der Goot, Barbara Plank
In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)

Paper Code Poster

Can Humans Identify Domains?

Maria Barrett*, Max Müller-Eberstein*, Elisa Bassignana*, Amalie Brogaard Pauli*, Mike Zhang*, Rob van der Goot*
In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
(*): equal contribution

Paper Code Poster Video

How to Encode Domain Information in Relation Classification

Elisa Bassignana, Viggo Unmack Gascou, Frida Nøhr Laustsen, Gustav Kristensen, Marie Haahr Petersen, Rob van der Goot, Barbara Plank
In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Paper Code Poster Video

Silver Syntax Pre-training for Cross-Domain Relation Extraction

Elisa Bassignana, Filip Ginter, Sampo Pyysalo, Rob van der Goot, and Barbara Plank
In Findings of the Association for Computational Linguistics: ACL 2023

Paper Code Poster Video

Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction

Elisa Bassignana, Filip Ginter, Sampo Pyysalo, Rob van der Goot, and Barbara Plank
In Proceedings of the 24rd Nordic Conference on Computational Linguistics (NoDaLiDa)

Paper Code Poster

CrossRE: A Cross-Domain Dataset for Relation Extraction

Elisa Bassignana and Barbara Plank
In Findings of the Association for Computational Linguistics: EMNLP 2022

Paper Code Video

Experimental Standards for Deep Learning in Natural Language Processing Research

Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Rob van der Goot, Christian Hardmeier, and Barbara Plank
In Findings of the Association for Computational Linguistics: EMNLP 2022

Paper Code Video

Evidence > Intuition: Transferability Estimation for Encoder Selection

Elisa Bassignana*, Max Müller-Eberstein*, Mike Zhang*, and Barbara Plank
In Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)
(*): equal contribution

Paper Code Video Poster

What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification

Elisa Bassignana and Barbara Plank
In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (SWR-ACL 2022)

Paper Video

Experimental Standards for Deep Learning in Natural Language Processing Research

Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Christian Hardmeier, and Barbara Plank
Machine Learning Evaluation Standards at ICLR 2022 (SMILES)
Received Outstanding paper award

Paper Code Video

Personal-ITY: A Novel YouTube-based Corpus for Personality Prediction in Italian

Elisa Bassignana, Malvina Nissim, Viviana Patti
In Proceedings of the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020)

Paper Code

Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality

Elisa Bassignana, Malvina Nissim, Viviana Patti
In Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media (PEOPLES 2020)

Paper

Hurtlex: A Multilingual Lexicon of Words to Hurt

Elisa Bassignana, Valerio Basile, Viviana Patti
In Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018)

Paper Code