@inproceedings{moscato-etal-2025-mnlp,
title = "{MNLP}@Multilingual Counterspeech Generation: Evaluating Translation and Background Knowledge Filtering",
author = "Moscato, Emanuele and
Muti, Arianna and
Nozza, Debora",
editor = "Bonaldi, Helena and
Vallecillo-Rodr{\'i}guez, Mar{\'i}a Estrella and
Zubiaga, Irune and
Montejo-R{\'a}ez, Arturo and
Soroa, Aitor and
Mart{\'i}n-Valdivia, Mar{\'i}a Teresa and
Guerini, Marco and
Agerri, Rodrigo",
booktitle = "Proceedings of the First Workshop on Multilingual Counterspeech Generation",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.mcg-1.7/",
pages = "56--64",
abstract = "We describe our participation in the Multilingual Counterspeech Generation shared task, which aims to generate a counternarrative to counteract hate speech, given a hateful sentence and relevant background knowledge. Our team tested two different aspects: translating outputs from English vs generating outputs in the original languages and filtering pieces of the background knowledge provided vs including all the background knowledge. Our experiments show that filtering the background knowledge in the same prompt and leaving data in the original languages leads to more adherent counternarrative generations, except for Basque, where translating the output from English and filtering the background knowledge in a separate prompt yields better results. Our system ranked first in English, Italian, and Spanish and fourth in Basque."
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="moscato-etal-2025-mnlp">
<titleInfo>
<title>MNLP@Multilingual Counterspeech Generation: Evaluating Translation and Background Knowledge Filtering</title>
</titleInfo>
<name type="personal">
<namePart type="given">Emanuele</namePart>
<namePart type="family">Moscato</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Arianna</namePart>
<namePart type="family">Muti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Debora</namePart>
<namePart type="family">Nozza</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-01</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the First Workshop on Multilingual Counterspeech Generation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Helena</namePart>
<namePart type="family">Bonaldi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">María</namePart>
<namePart type="given">Estrella</namePart>
<namePart type="family">Vallecillo-Rodríguez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Irune</namePart>
<namePart type="family">Zubiaga</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Arturo</namePart>
<namePart type="family">Montejo-Ráez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aitor</namePart>
<namePart type="family">Soroa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">María</namePart>
<namePart type="given">Teresa</namePart>
<namePart type="family">Martín-Valdivia</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marco</namePart>
<namePart type="family">Guerini</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rodrigo</namePart>
<namePart type="family">Agerri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Abu Dhabi, UAE</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>We describe our participation in the Multilingual Counterspeech Generation shared task, which aims to generate a counternarrative to counteract hate speech, given a hateful sentence and relevant background knowledge. Our team tested two different aspects: translating outputs from English vs generating outputs in the original languages and filtering pieces of the background knowledge provided vs including all the background knowledge. Our experiments show that filtering the background knowledge in the same prompt and leaving data in the original languages leads to more adherent counternarrative generations, except for Basque, where translating the output from English and filtering the background knowledge in a separate prompt yields better results. Our system ranked first in English, Italian, and Spanish and fourth in Basque.</abstract>
<identifier type="citekey">moscato-etal-2025-mnlp</identifier>
<location>
<url>https://aclanthology.org/2025.mcg-1.7/</url>
</location>
<part>
<date>2025-01</date>
<extent unit="page">
<start>56</start>
<end>64</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T MNLP@Multilingual Counterspeech Generation: Evaluating Translation and Background Knowledge Filtering
%A Moscato, Emanuele
%A Muti, Arianna
%A Nozza, Debora
%Y Bonaldi, Helena
%Y Vallecillo-Rodríguez, María Estrella
%Y Zubiaga, Irune
%Y Montejo-Ráez, Arturo
%Y Soroa, Aitor
%Y Martín-Valdivia, María Teresa
%Y Guerini, Marco
%Y Agerri, Rodrigo
%S Proceedings of the First Workshop on Multilingual Counterspeech Generation
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F moscato-etal-2025-mnlp
%X We describe our participation in the Multilingual Counterspeech Generation shared task, which aims to generate a counternarrative to counteract hate speech, given a hateful sentence and relevant background knowledge. Our team tested two different aspects: translating outputs from English vs generating outputs in the original languages and filtering pieces of the background knowledge provided vs including all the background knowledge. Our experiments show that filtering the background knowledge in the same prompt and leaving data in the original languages leads to more adherent counternarrative generations, except for Basque, where translating the output from English and filtering the background knowledge in a separate prompt yields better results. Our system ranked first in English, Italian, and Spanish and fourth in Basque.
%U https://aclanthology.org/2025.mcg-1.7/
%P 56-64
Markdown (Informal)
[MNLP@Multilingual Counterspeech Generation: Evaluating Translation and Background Knowledge Filtering](https://aclanthology.org/2025.mcg-1.7/) (Moscato et al., MCG 2025)
ACL