Papers by Teresa Lynn
gaBERT — an Irish Language Model (2022.lrec-1)
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James Barry, Joachim Wagner, Lauren Cassidy, Alan Cowap, Teresa Lynn, Abigail Walsh, Mícheál J. Ó Meachair, Jennifer Foster
| Challenge: | We compare gaBERT to multilingual BERT and the monolingual Irish WikiBERT and show that gaBERt provides better representations for downstream parsing tasks. |
| Approach: | They propose a monolingual BERT model for the Irish language that provides better representations for a downstream parsing task. |
| Outcome: | The proposed model performs better than the multilingual BERT and the monolingual Irish WikiBERT on a parsing task. |
Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies (2020.lrec-1)
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Manuela Sanguinetti, Cristina Bosco, Lauren Cassidy, Özlem Çetinoğlu, Alessandra Teresa Cignarella, Teresa Lynn, Ines Rehbein, Josef Ruppenhofer, Djamé Seddah, Amir Zeldes
| Challenge: | Despite the increasing number of contributions on Part-of-Speech tagging and parsing, automatic processing of user-generated content (UGC) still represents a challenging task. |
| Approach: | They propose a set of guidelines for the annotation of user-generated texts within the Universal Dependencies framework. |
| Outcome: | The proposed annotation guidelines promote cross-linguistic consistency, which has always been in the spirit of UD. |
From Multiple-Choice to Extractive QA: A Case Study for English and Arabic (2025.coling-main)
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Teresa Lynn, Malik H. Altakrori, Samar M. Magdy, Rocktim Jyoti Das, Chenyang Lyu, Mohamed Nasr, Younes Samih, Kirill Chirkunov, Alham Fikri Aji, Preslav Nakov, Shantanu Godbole, Salim Roukos, Radu Florian, Nizar Habash
| Challenge: | Recent years have brought about very fast developments in Natural Language Processing (NLP), but many other languages are overlooked due to limited resources. |
| Approach: | They propose to repurpose a multilingual BELEBELE dataset for a task of extractive QA in the style of machine reading comprehension. |
| Outcome: | The proposed approach could be used to extract QA in the style of machine reading comprehension. |
TwittIrish: A Universal Dependencies Treebank of Tweets in Modern Irish (2022.acl-long)
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| Challenge: | Modern Irish is a minority language lacking computational resources for accurate automatic syntactic parsing of user-generated content. |
| Approach: | They propose to use a treebank to facilitate natural language parsing of user-generated content in Irish. |
| Outcome: | The proposed treebank enables natural language processing of user-generated content in Irish. |
A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models (2024.lrec-main)
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Chenyang Lyu, Zefeng Du, Jitao Xu, Yitao Duan, Minghao Wu, Teresa Lynn, Alham Fikri Aji, Derek F. Wong, Longyue Wang
| Challenge: | Large Language Models (LLMs) are introducing a new phase in machine translation . despite advances in MT, there are still many challenges to overcome . |
| Approach: | They propose to highlight several new directions for MT that are influenced by Large Language Models like GPT-4 and ChatGPT. |
| Outcome: | The proposed models offer vast linguistic understandings and bring innovative methodologies, such as prompt-based techniques, that have the potential to further elevate MT. |