Papers by Laura Vásquez-Rodríguez

2 papers
Investigating Text Simplification Evaluation (2021.findings-acl)

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Challenge: Existing studies show that parallel TS corpora contain inaccurate simplifications and incorrect alignments.
Approach: They propose to improve the distribution of parallel text simplification corpora to build more robust TS models.
Outcome: The proposed models can be improved by improving the distribution of TS datasets.
BLESS: Benchmarking Large Language Models on Sentence Simplification (2023.emnlp-main)

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Challenge: BLESS is a performance benchmark of the most recent state-of-the-art Large Language Models (LLMs) on the task of text simplification (TS).
Approach: They present a performance benchmark of the most recent state-of-the-art Large Language Models (LLMs) on the task of text simplification (TS).
Outcome: The proposed benchmarks show that the most recent state-of-the-art LLMs perform better on the task of text simplification (TS).

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