Papers by Antonio David Ponce Martínez

2 papers
Automating Easy Read Text Segmentation (2024.findings-emnlp)

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Challenge: Existing methods for automatic segmentation of Easy Read text have not been explored in detail.
Approach: They propose automated methods for Easy Read segmentation that leverage masked and generative language models and constituent parsing to evaluate their viability.
Outcome: The proposed methods are compared with human-driven segmentation in three languages.
Split and Rephrase with Large Language Models (2024.acl-long)

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Challenge: Split and Rephrase (SPRP) tasks require modelling complex grammatical aspects to provide optimal splits and appropriate rephrasing.
Approach: They evaluate large language models on the Split and Rephrase task . they show they can provide large improvements over the state of the art on main metrics .
Outcome: The proposed model outperforms the state-of-the-art model on the Split and Rephrase task on the main metric, but still lacks in splitting compliance.

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