@inproceedings{pezo-etal-2025-ipezotu,
title = "ipezo{TU} at {S}em{E}val-2025 Task 7: Hybrid Ensemble Retrieval for Multilingual Fact-Checking",
author = "Pezo, Iva and
Hanbury, Allan and
Staudinger, Moritz",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.153/",
pages = "1159--1167",
ISBN = "979-8-89176-273-2",
abstract = "Fact-check retrieval plays a crucial role in combating misinformation by ensuring that claims are accurately matched with relevant fact-checks. In this work, we present a hybrid retrieval pipeline that integrates lexical and semantic retrieval models, leveraging their complementary strengths. We evaluate different retrieval and reranking strategies, demonstrating that hybrid ensembling consistently outperforms individual models, while reranking provides only marginal improvements."
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<abstract>Fact-check retrieval plays a crucial role in combating misinformation by ensuring that claims are accurately matched with relevant fact-checks. In this work, we present a hybrid retrieval pipeline that integrates lexical and semantic retrieval models, leveraging their complementary strengths. We evaluate different retrieval and reranking strategies, demonstrating that hybrid ensembling consistently outperforms individual models, while reranking provides only marginal improvements.</abstract>
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%0 Conference Proceedings
%T ipezoTU at SemEval-2025 Task 7: Hybrid Ensemble Retrieval for Multilingual Fact-Checking
%A Pezo, Iva
%A Hanbury, Allan
%A Staudinger, Moritz
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F pezo-etal-2025-ipezotu
%X Fact-check retrieval plays a crucial role in combating misinformation by ensuring that claims are accurately matched with relevant fact-checks. In this work, we present a hybrid retrieval pipeline that integrates lexical and semantic retrieval models, leveraging their complementary strengths. We evaluate different retrieval and reranking strategies, demonstrating that hybrid ensembling consistently outperforms individual models, while reranking provides only marginal improvements.
%U https://aclanthology.org/2025.semeval-1.153/
%P 1159-1167
Markdown (Informal)
[ipezoTU at SemEval-2025 Task 7: Hybrid Ensemble Retrieval for Multilingual Fact-Checking](https://aclanthology.org/2025.semeval-1.153/) (Pezo et al., SemEval 2025)
ACL