ACL-rlg: A Dataset for Reading List Generation - Archive ouverte HAL
Communication Dans Un Congrès Année : 2025

ACL-rlg: A Dataset for Reading List Generation

Résumé

Familiarizing oneself with a new scientific field and its existing literature can be daunting due to the large amount of available articles. Curated lists of academic references, or reading lists, compiled by experts, offer a structured way to gain a comprehensive overview of a domain or a specific scientific challenge. In this work, we introduce ACL-rlg, the largest open expert-annotated reading list dataset. We also provide multiple baselines for evaluating reading list generation and formally define it as a retrieval task. Our qualitative study highlights the fact that traditional scholarly search engines and indexing methods perform poorly on this task, and GPT-4o, despite showing better results, exhibits signs of potential data contamination.
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Dates et versions

hal-04852617 , version 1 (27-12-2024)

Identifiants

  • HAL Id : hal-04852617 , version 1

Citer

Julien Aubert-Béduchaud, Florian Boudin, Béatrice Daille, Richard Dufour. ACL-rlg: A Dataset for Reading List Generation. The 31st International Conference on Computational Linguistics, Jan 2025, Abu Dhabi, United Arab Emirates. ⟨hal-04852617⟩
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