Papers by Elena Epure

4 papers
Improving Quotation Attribution with Fictional Character Embeddings (2024.findings-emnlp)

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Challenge: Recent methods to attribute quotes to human logic lack character representations, which often leads to errors in more challenging examples of attribution: anaphoric and implicit quotes.
Approach: They propose to augment a popular quotation attribution system, BookNLP, with character embeddings that encode global stylistic information of characters derived from an off-the-shelf stylometric model, Universal Authorship Representation (UAR).
Outcome: The proposed system improves anaphoric and implicit quotes, reaching state-of-the-art.
A Human Subject Study of Named Entity Recognition in Conversational Music Recommendation Queries (2023.eacl-main)

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Challenge: NER is a complex task that requires a high degree of precision and a higher level of recall.
Approach: They evaluated the human NER linguistic behaviour on a noisy corpus of conversational music recommendation queries with many irregular and novel named entities.
Outcome: The results show that human NER was hard to perform under a strict evaluation schema and that the model had higher recall because of entity exposure.
Data-Efficient Playlist Captioning With Musical and Linguistic Knowledge (2022.emnlp-main)

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Challenge: Music streaming services feature billions of playlists created by users, professional editors or algorithms.
Approach: They propose a multi-modal encoder-decoder model for automatic playlist captioning that leverages linguistic and musical knowledge to generate correct and thematic captions.
Outcome: The proposed model yields 2x-3x higher BLEU@4 and CIDEr than state-of-the-art captioning algorithms on a new playlists dataset from two major streaming services.
Automatic Annotation of Direct Speech in Written French Narratives (2023.acl-long)

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Challenge: a new framework for AADS annotation in written text is needed for literary studies.
Approach: They propose to use automatic annotation of direct speech (AADS) in written text to compare works by different authors . they adapted a large-to-date French narrative dataset annotated with DS per word .
Outcome: The proposed framework is a step further to encourage more research on the topic.

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