Team LA at SCIDOCA shared task 2025: Citation Discovery via relation-based zero-shot retrieval

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Autori principali: An, Trieu, Nguyen, Long, Nguyen, Minh Le
Natura: Preprint
Pubblicazione: 2025
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author An, Trieu
Nguyen, Long
Nguyen, Minh Le
author_facet An, Trieu
Nguyen, Long
Nguyen, Minh Le
contents The Citation Discovery Shared Task focuses on predicting the correct citation from a given candidate pool for a given paragraph. The main challenges stem from the length of the abstract paragraphs and the high similarity among candidate abstracts, making it difficult to determine the exact paper to cite. To address this, we develop a system that first retrieves the top-k most similar abstracts based on extracted relational features from the given paragraph. From this subset, we leverage a Large Language Model (LLM) to accurately identify the most relevant citation. We evaluate our framework on the training dataset provided by the SCIDOCA 2025 organizers, demonstrating its effectiveness in citation prediction.
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institution arXiv
publishDate 2025
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spellingShingle Team LA at SCIDOCA shared task 2025: Citation Discovery via relation-based zero-shot retrieval
An, Trieu
Nguyen, Long
Nguyen, Minh Le
Information Retrieval
Computation and Language
The Citation Discovery Shared Task focuses on predicting the correct citation from a given candidate pool for a given paragraph. The main challenges stem from the length of the abstract paragraphs and the high similarity among candidate abstracts, making it difficult to determine the exact paper to cite. To address this, we develop a system that first retrieves the top-k most similar abstracts based on extracted relational features from the given paragraph. From this subset, we leverage a Large Language Model (LLM) to accurately identify the most relevant citation. We evaluate our framework on the training dataset provided by the SCIDOCA 2025 organizers, demonstrating its effectiveness in citation prediction.
title Team LA at SCIDOCA shared task 2025: Citation Discovery via relation-based zero-shot retrieval
topic Information Retrieval
Computation and Language
url https://arxiv.org/abs/2506.18316