Papers by Lydia Nishimwe

1 papers
Making Sentence Embeddings Robust to User-Generated Content (2024.lrec-main)

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Challenge: NLP models struggle on user-generated content (UGC) due to high lexical variance and deviating from the standard texts.
Approach: They propose a sentence embedding model that embeds non-standard sentences and their standard counterparts close to each other in the embeddable space.
Outcome: The proposed model outperforms LASER on key typos and social media abbreviations while outperforming LASER in other tasks.

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