@inproceedings{ghahroodi-etal-2023-sina,
title = "Sina at {S}em{E}val-2023 Task 4: A Class-Token Attention-based Model for Human Value Detection",
author = "Ghahroodi, Omid and
Sadraei Javaheri, Mohammad Ali and
Dastgheib, Doratossadat and
Soleymani Baghshah, Mahdieh and
Rohban, Mohammad Hossein and
Rabiee, Hamid and
Asgari, Ehsaneddin",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.299",
doi = "10.18653/v1/2023.semeval-1.299",
pages = "2164--2167",
abstract = "The human values expressed in argumentative texts can provide valuable insights into the culture of a society. They can be helpful in various applications such as value-based profiling and ethical analysis. However, one of the first steps in achieving this goal is to detect the category of human value from an argument accurately. This task is challenging due to the lack of data and the need for philosophical inference. It also can be challenging for humans to classify arguments according to their underlying human values. This paper elaborates on our model for the SemEval 2023 Task 4 on human value detection. We propose a class-token attention-based model and evaluate it against baseline models, including finetuned BERT language model and a keyword-based approach.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ghahroodi-etal-2023-sina">
<titleInfo>
<title>Sina at SemEval-2023 Task 4: A Class-Token Attention-based Model for Human Value Detection</title>
</titleInfo>
<name type="personal">
<namePart type="given">Omid</namePart>
<namePart type="family">Ghahroodi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mohammad</namePart>
<namePart type="given">Ali</namePart>
<namePart type="family">Sadraei Javaheri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Doratossadat</namePart>
<namePart type="family">Dastgheib</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mahdieh</namePart>
<namePart type="family">Soleymani Baghshah</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mohammad</namePart>
<namePart type="given">Hossein</namePart>
<namePart type="family">Rohban</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hamid</namePart>
<namePart type="family">Rabiee</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ehsaneddin</namePart>
<namePart type="family">Asgari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Atul</namePart>
<namePart type="given">Kr.</namePart>
<namePart type="family">Ojha</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">A</namePart>
<namePart type="given">Seza</namePart>
<namePart type="family">Doğruöz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Giovanni</namePart>
<namePart type="family">Da San Martino</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Harish</namePart>
<namePart type="family">Tayyar Madabushi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ritesh</namePart>
<namePart type="family">Kumar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elisa</namePart>
<namePart type="family">Sartori</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Toronto, Canada</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>The human values expressed in argumentative texts can provide valuable insights into the culture of a society. They can be helpful in various applications such as value-based profiling and ethical analysis. However, one of the first steps in achieving this goal is to detect the category of human value from an argument accurately. This task is challenging due to the lack of data and the need for philosophical inference. It also can be challenging for humans to classify arguments according to their underlying human values. This paper elaborates on our model for the SemEval 2023 Task 4 on human value detection. We propose a class-token attention-based model and evaluate it against baseline models, including finetuned BERT language model and a keyword-based approach.</abstract>
<identifier type="citekey">ghahroodi-etal-2023-sina</identifier>
<identifier type="doi">10.18653/v1/2023.semeval-1.299</identifier>
<location>
<url>https://aclanthology.org/2023.semeval-1.299</url>
</location>
<part>
<date>2023-07</date>
<extent unit="page">
<start>2164</start>
<end>2167</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Sina at SemEval-2023 Task 4: A Class-Token Attention-based Model for Human Value Detection
%A Ghahroodi, Omid
%A Sadraei Javaheri, Mohammad Ali
%A Dastgheib, Doratossadat
%A Soleymani Baghshah, Mahdieh
%A Rohban, Mohammad Hossein
%A Rabiee, Hamid
%A Asgari, Ehsaneddin
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ghahroodi-etal-2023-sina
%X The human values expressed in argumentative texts can provide valuable insights into the culture of a society. They can be helpful in various applications such as value-based profiling and ethical analysis. However, one of the first steps in achieving this goal is to detect the category of human value from an argument accurately. This task is challenging due to the lack of data and the need for philosophical inference. It also can be challenging for humans to classify arguments according to their underlying human values. This paper elaborates on our model for the SemEval 2023 Task 4 on human value detection. We propose a class-token attention-based model and evaluate it against baseline models, including finetuned BERT language model and a keyword-based approach.
%R 10.18653/v1/2023.semeval-1.299
%U https://aclanthology.org/2023.semeval-1.299
%U https://doi.org/10.18653/v1/2023.semeval-1.299
%P 2164-2167
Markdown (Informal)
[Sina at SemEval-2023 Task 4: A Class-Token Attention-based Model for Human Value Detection](https://aclanthology.org/2023.semeval-1.299) (Ghahroodi et al., SemEval 2023)
ACL