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Teresa Lynn

4 accepted papers

2025

From Multiple-Choice to Extractive QA: A Case Study for English and Arabic

COLING 2025main

The rapid evolution of Natural Language Processing (NLP) has favoured major languages such as English, leaving a significant gap for many others due to limited resources. This is especially evident in the context of data annotation, a task whose importance cannot be underestimated, but which is time…

2024

A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

COLING 2024main

Machine Translation (MT) has greatly advanced over the years due to the developments in deep neural networks. However, the emergence of Large Language Models (LLMs) like GPT-4 and ChatGPT is introducing a new phase in the MT domain. In this context, we believe that the future of MT is intricately ti…

Cited by 16SourcePDFScholar
2024

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

NeurIPS 2024oral

Visual Question Answering~(VQA) is an important task in multimodal AI, which requires models to understand and reason on knowledge present in visual and textual data. However, most of the current VQA datasets and models are primarily focused on English and a few major world languages, with images th…

Cited by 34SourcePDFScholar
2022

TwittIrish: A Universal Dependencies Treebank of Tweets in Modern Irish

ACL 2022long

Modern Irish is a minority language lacking sufficient computational resources for the task of accurate automatic syntactic parsing of user-generated content such as tweets. Although language technology for the Irish language has been developing in recent years, these tools tend to perform poorly on…