LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text

Pranav Gupta; Souvik Bhattacharyya; Niranjan Kumar M; Billodal Roy

doi:10.18653/v1/2025.calcs-1.6

LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text

Pranav Gupta, Souvik Bhattacharyya, Niranjan Kumar M, Billodal Roy

Correct Metadata for

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

Code-switched generation is an emerging application in NLP systems, as code-switched text and speech are common and natural forms of conversation in multilingual communities worldwide. While monolingual generation has matured significantly with advances in large language models, code-switched generation still remains challenging, especially for languages and domains with less representation in pre-training datasets. In this paper, we describe our submission to the shared task of predicting human preferences for code-switched text in English-Malayalam, English-Tamil, and English-Hindi. We discuss our various approaches and report on the accuracy scores for each approach.

Anthology ID:: 2025.calcs-1.6
Volume:: Proceedings of the 7th Workshop on Computational Approaches to Linguistic Code-Switching
Month:: May
Year:: 2025
Address:: Albuquerque, New Mexico, USA
Editors:: Genta Indra Winata, Sudipta Kar, Marina Zhukova, Thamar Solorio, Xi Ai, Injy Hamed, Mahardika Krisna Krisna Ihsani, Derry Tanti Wijaya, Garry Kuwanto
Venues:: CALCS | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 48–53
Language:
URL:: https://aclanthology.org/2025.calcs-1.6/
DOI:: 10.18653/v1/2025.calcs-1.6
Bibkey:
Cite (ACL):: Pranav Gupta, Souvik Bhattacharyya, Niranjan Kumar M, and Billodal Roy. 2025. LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text. In Proceedings of the 7th Workshop on Computational Approaches to Linguistic Code-Switching, pages 48–53, Albuquerque, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):: LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text (Gupta et al., CALCS 2025)
Copy Citation:
PDF:: https://aclanthology.org/2025.calcs-1.6.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{gupta-etal-2025-lexilogic,
    title = "{L}exi{L}ogic@{CALCS} 2025: Predicting Preferences in Generated Code-Switched Text",
    author = "Gupta, Pranav  and
      Bhattacharyya, Souvik  and
      M, Niranjan Kumar  and
      Roy, Billodal",
    editor = "Winata, Genta Indra  and
      Kar, Sudipta  and
      Zhukova, Marina  and
      Solorio, Thamar  and
      Ai, Xi  and
      Hamed, Injy  and
      Ihsani, Mahardika Krisna Krisna  and
      Wijaya, Derry Tanti  and
      Kuwanto, Garry",
    booktitle = "Proceedings of the 7th Workshop on Computational Approaches to Linguistic Code-Switching",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.calcs-1.6/",
    doi = "10.18653/v1/2025.calcs-1.6",
    pages = "48--53",
    ISBN = "979-8-89176-053-0",
    abstract = "Code-switched generation is an emerging application in NLP systems, as code-switched text and speech are common and natural forms of conversation in multilingual communities worldwide. While monolingual generation has matured significantly with advances in large language models, code-switched generation still remains challenging, especially for languages and domains with less representation in pre-training datasets. In this paper, we describe our submission to the shared task of predicting human preferences for code-switched text in English-Malayalam, English-Tamil, and English-Hindi. We discuss our various approaches and report on the accuracy scores for each approach."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gupta-etal-2025-lexilogic">
    <titleInfo>
        <title>LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Pranav</namePart>
        <namePart type="family">Gupta</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Souvik</namePart>
        <namePart type="family">Bhattacharyya</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Niranjan</namePart>
        <namePart type="given">Kumar</namePart>
        <namePart type="family">M</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Billodal</namePart>
        <namePart type="family">Roy</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-05</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 7th Workshop on Computational Approaches to Linguistic Code-Switching</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Genta</namePart>
            <namePart type="given">Indra</namePart>
            <namePart type="family">Winata</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sudipta</namePart>
            <namePart type="family">Kar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Marina</namePart>
            <namePart type="family">Zhukova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Thamar</namePart>
            <namePart type="family">Solorio</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xi</namePart>
            <namePart type="family">Ai</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Injy</namePart>
            <namePart type="family">Hamed</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mahardika</namePart>
            <namePart type="given">Krisna</namePart>
            <namePart type="given">Krisna</namePart>
            <namePart type="family">Ihsani</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Derry</namePart>
            <namePart type="given">Tanti</namePart>
            <namePart type="family">Wijaya</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Garry</namePart>
            <namePart type="family">Kuwanto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Albuquerque, New Mexico, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-053-0</identifier>
    </relatedItem>
    <abstract>Code-switched generation is an emerging application in NLP systems, as code-switched text and speech are common and natural forms of conversation in multilingual communities worldwide. While monolingual generation has matured significantly with advances in large language models, code-switched generation still remains challenging, especially for languages and domains with less representation in pre-training datasets. In this paper, we describe our submission to the shared task of predicting human preferences for code-switched text in English-Malayalam, English-Tamil, and English-Hindi. We discuss our various approaches and report on the accuracy scores for each approach.</abstract>
    <identifier type="citekey">gupta-etal-2025-lexilogic</identifier>
    <identifier type="doi">10.18653/v1/2025.calcs-1.6</identifier>
    <location>
        <url>https://aclanthology.org/2025.calcs-1.6/</url>
    </location>
    <part>
        <date>2025-05</date>
        <extent unit="page">
            <start>48</start>
            <end>53</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text
%A Gupta, Pranav
%A Bhattacharyya, Souvik
%A M, Niranjan Kumar
%A Roy, Billodal
%Y Winata, Genta Indra
%Y Kar, Sudipta
%Y Zhukova, Marina
%Y Solorio, Thamar
%Y Ai, Xi
%Y Hamed, Injy
%Y Ihsani, Mahardika Krisna Krisna
%Y Wijaya, Derry Tanti
%Y Kuwanto, Garry
%S Proceedings of the 7th Workshop on Computational Approaches to Linguistic Code-Switching
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico, USA
%@ 979-8-89176-053-0
%F gupta-etal-2025-lexilogic
%X Code-switched generation is an emerging application in NLP systems, as code-switched text and speech are common and natural forms of conversation in multilingual communities worldwide. While monolingual generation has matured significantly with advances in large language models, code-switched generation still remains challenging, especially for languages and domains with less representation in pre-training datasets. In this paper, we describe our submission to the shared task of predicting human preferences for code-switched text in English-Malayalam, English-Tamil, and English-Hindi. We discuss our various approaches and report on the accuracy scores for each approach.
%R 10.18653/v1/2025.calcs-1.6
%U https://aclanthology.org/2025.calcs-1.6/
%U https://doi.org/10.18653/v1/2025.calcs-1.6
%P 48-53

Download as File

Markdown (Informal)

[LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text](https://aclanthology.org/2025.calcs-1.6/) (Gupta et al., CALCS 2025)

LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text (Gupta et al., CALCS 2025)

ACL

Pranav Gupta, Souvik Bhattacharyya, Niranjan Kumar M, and Billodal Roy. 2025. LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text. In Proceedings of the 7th Workshop on Computational Approaches to Linguistic Code-Switching, pages 48–53, Albuquerque, New Mexico, USA. Association for Computational Linguistics.