<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="rabehi-etal-2026-team">
    <titleInfo>
        <title>Team Macaroni at SemEval-2026 Task 10: PsyCoMark: Psycholinguistic Conspiracy Marker Extraction and Detection</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Rofaida</namePart>
        <namePart type="family">Rabehi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Nicolai</namePart>
        <namePart type="family">Plenk</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Miriam</namePart>
        <namePart type="family">Han</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 20th International Workshop on Semantic Evaluation (2026)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Kochmar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Debanjan</namePart>
            <namePart type="family">Ghosh</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kai</namePart>
            <namePart type="family">North</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mamoru</namePart>
            <namePart type="family">Komachi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">San Diego, California, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-414-9</identifier>
    </relatedItem>
    <abstract>This paper describes our submission to SemEval-2026 Task 10: PsyCoMark, which addresses span-level identification of psycholinguistic conspiracy markers and document-level conspiracy classification. For Subtask 1, we fine-tune several pretrained transformer encoders and analyse their behaviour under different training configurations. For Subtask 2, we develop a hybrid system that combines ModernBERT-large with surface-level linguistic features.Our results show that straightforward fine-tuning of strong pretrained models is more effective than more complex pipelines and that additional handcrafted features do not yield consistent improvements. On the official test set, we rank 18th in Subtask 1 (overlap-based macro F1 = 0.16) and 20th in Subtask 2 (macro F1 = 0.76).</abstract>
    <identifier type="citekey">rabehi-etal-2026-team</identifier>
    <location>
        <url>https://aclanthology.org/2026.semeval-1.50/</url>
    </location>
    <part>
        <date>2026-07</date>
        <extent unit="page">
            <start>338</start>
            <end>342</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Team Macaroni at SemEval-2026 Task 10: PsyCoMark: Psycholinguistic Conspiracy Marker Extraction and Detection
%A Rabehi, Rofaida
%A Plenk, Nicolai
%A Han, Miriam
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F rabehi-etal-2026-team
%X This paper describes our submission to SemEval-2026 Task 10: PsyCoMark, which addresses span-level identification of psycholinguistic conspiracy markers and document-level conspiracy classification. For Subtask 1, we fine-tune several pretrained transformer encoders and analyse their behaviour under different training configurations. For Subtask 2, we develop a hybrid system that combines ModernBERT-large with surface-level linguistic features.Our results show that straightforward fine-tuning of strong pretrained models is more effective than more complex pipelines and that additional handcrafted features do not yield consistent improvements. On the official test set, we rank 18th in Subtask 1 (overlap-based macro F1 = 0.16) and 20th in Subtask 2 (macro F1 = 0.76).
%U https://aclanthology.org/2026.semeval-1.50/
%P 338-342

Markdown (Informal)

[Team Macaroni at SemEval-2026 Task 10: PsyCoMark: Psycholinguistic Conspiracy Marker Extraction and Detection](https://aclanthology.org/2026.semeval-1.50/) (Rabehi et al., SemEval 2026)

• Team Macaroni at SemEval-2026 Task 10: PsyCoMark: Psycholinguistic Conspiracy Marker Extraction and Detection (Rabehi et al., SemEval 2026)

ACL

• Rofaida Rabehi, Nicolai Plenk, and Miriam Han. 2026. Team Macaroni at SemEval-2026 Task 10: PsyCoMark: Psycholinguistic Conspiracy Marker Extraction and Detection. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 338–342, San Diego, California, USA. Association for Computational Linguistics.