@inproceedings{albarede-etal-2023-entity,
title = "Entity Enhanced Attention Graph-Based Passages Retrieval",
author = "Albarede, Lucas and
Goeuriot, Lorraine and
Mulhem, Philippe and
Le Pape-Gardeux, Claude and
Marie, Sylvain and
Chardin-Segui, Trinidad",
editor = {Zargayouna, Ha{\"i}fa},
booktitle = "Actes de CORIA-TALN 2023. Actes de la 18e Conf{\'e}rence en Recherche d`Information et Applications (CORIA)",
month = "6",
year = "2023",
address = "Paris, France",
publisher = "ATALA",
url = "https://aclanthology.org/2023.jeptalnrecital-coria.13/",
pages = "196--200",
abstract = "Passage retrieval is crucial in specialized domains where documents are long and complex, such as patents, legal documents, scientific reports, etc. We explore in this paper the integration of Entities and passages in Heterogeneous Attention Graph Models dedicated to passage retrieval. We use the two passage retrieval architectures based on re-ranking proposed in [1]. We experiment our proposal on the TREC CAR Y3 Passage Retrieval Task. The results obtained show an improvement over state-of-the-art techniques and proves the effectiveness of the approach. Our experiments also show the importance of using adequate parameters for such approach."
}
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<abstract>Passage retrieval is crucial in specialized domains where documents are long and complex, such as patents, legal documents, scientific reports, etc. We explore in this paper the integration of Entities and passages in Heterogeneous Attention Graph Models dedicated to passage retrieval. We use the two passage retrieval architectures based on re-ranking proposed in [1]. We experiment our proposal on the TREC CAR Y3 Passage Retrieval Task. The results obtained show an improvement over state-of-the-art techniques and proves the effectiveness of the approach. Our experiments also show the importance of using adequate parameters for such approach.</abstract>
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%0 Conference Proceedings
%T Entity Enhanced Attention Graph-Based Passages Retrieval
%A Albarede, Lucas
%A Goeuriot, Lorraine
%A Mulhem, Philippe
%A Le Pape-Gardeux, Claude
%A Marie, Sylvain
%A Chardin-Segui, Trinidad
%Y Zargayouna, Haïfa
%S Actes de CORIA-TALN 2023. Actes de la 18e Conférence en Recherche d‘Information et Applications (CORIA)
%D 2023
%8 June
%I ATALA
%C Paris, France
%F albarede-etal-2023-entity
%X Passage retrieval is crucial in specialized domains where documents are long and complex, such as patents, legal documents, scientific reports, etc. We explore in this paper the integration of Entities and passages in Heterogeneous Attention Graph Models dedicated to passage retrieval. We use the two passage retrieval architectures based on re-ranking proposed in [1]. We experiment our proposal on the TREC CAR Y3 Passage Retrieval Task. The results obtained show an improvement over state-of-the-art techniques and proves the effectiveness of the approach. Our experiments also show the importance of using adequate parameters for such approach.
%U https://aclanthology.org/2023.jeptalnrecital-coria.13/
%P 196-200
Markdown (Informal)
[Entity Enhanced Attention Graph-Based Passages Retrieval](https://aclanthology.org/2023.jeptalnrecital-coria.13/) (Albarede et al., JEP/TALN/RECITAL 2023)
ACL
- Lucas Albarede, Lorraine Goeuriot, Philippe Mulhem, Claude Le Pape-Gardeux, Sylvain Marie, and Trinidad Chardin-Segui. 2023. Entity Enhanced Attention Graph-Based Passages Retrieval. In Actes de CORIA-TALN 2023. Actes de la 18e Conférence en Recherche d'Information et Applications (CORIA), pages 196–200, Paris, France. ATALA.