Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation

Aygalic Jara-Mikolajczak; Thomas Lavergne; Sophie Rosset

Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation

Aygalic Jara–Mikolajczak, Thomas Lavergne, Sophie Rosset

Correct Metadata for

Use this form to create a GitHub issue with structured data describing the correction. You will need a GitHub account. Once you create that issue, the correction will be reviewed by a staff member.

⚠️ Mobile Users: Submitting this form to create a new issue will only work with github.com, not the GitHub Mobile app.

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>. You may use ... for bold, ... for italic, ... for underline, <sc>...</sc> for small-caps, <tt>...<tt> for typewriter text, <url>...</url> for URLs, <a href=...> for hyperlinks, and <par/> for paragraph breaks.

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

We describe a multilingual, character-level hallucination detection system for vision-language models combining multi-layer hidden states, text-to-vision LoRA transfer, multitask learning, and language-specific span emission. Our submission achieved a validation Character AUPRC of 0.5530 and an average test Cor/Cor+lbl of 0.5243/0.4174. A controlled post-submission factorial analysis improved validation Character AUPRC to 0.5595. Team champ placed third in French, fourth in Italian and Chinese, and fifth in English.

Anthology ID:: 2026.uncertainlp-main.62
Volume:: The Proceedings of the Third Workshop on Uncertainty-Aware NLP
Month:: October
Year:: 2026
Address:: Budapest, Hungary
Editors:: Wilker Aziz, Jonathan Berant, Bryan Eikema, Evgenia Ilia, Marie-Catherine de Marneffe, Barbara Plank, Artem Shelmanov, Swabha Swayamdipta, Jörg Tiedemann, Artem Vazhentsev, Raúl Vázquez, Chrysoula Zerva
Venues:: UncertaiNLP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 856–862
Language:
URL:: https://aclanthology.org/2026.uncertainlp-main.62/
DOI:
Bibkey:
Cite (ACL):: Aygalic Jara–Mikolajczak, Thomas Lavergne, and Sophie Rosset. 2026. Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation. In The Proceedings of the Third Workshop on Uncertainty-Aware NLP, pages 856–862, Budapest, Hungary. Association for Computational Linguistics.
Cite (Informal):: Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation (Jara–Mikolajczak et al., UncertaiNLP 2026)
Copy Citation:
PDF:: https://aclanthology.org/2026.uncertainlp-main.62.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{jara-mikolajczak-etal-2026-team,
    title = "Team champ at {SHROOM}-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation",
    author = "Jara{--}Mikolajczak, Aygalic  and
      Lavergne, Thomas  and
      Rosset, Sophie",
    editor = {Aziz, Wilker  and
      Berant, Jonathan  and
      Eikema, Bryan  and
      Ilia, Evgenia  and
      de Marneffe, Marie-Catherine  and
      Plank, Barbara  and
      Shelmanov, Artem  and
      Swayamdipta, Swabha  and
      Tiedemann, J{\"o}rg  and
      Vazhentsev, Artem  and
      V{\'a}zquez, Ra{\'u}l  and
      Zerva, Chrysoula},
    booktitle = "The Proceedings of the Third Workshop on Uncertainty-Aware {NLP}",
    month = oct,
    year = "2026",
    address = "Budapest, Hungary",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.uncertainlp-main.62/",
    pages = "856--862",
    ISBN = "979-8-89176-486-6",
    abstract = "We describe a multilingual, character-level hallucination detection system for vision-language models combining multi-layer hidden states, text-to-vision LoRA transfer, multitask learning, and language-specific span emission. Our submission achieved a validation Character AUPRC of 0.5530 and an average test Cor/Cor+lbl of 0.5243/0.4174. A controlled post-submission factorial analysis improved validation Character AUPRC to 0.5595. Team champ placed third in French, fourth in Italian and Chinese, and fifth in English."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="jara-mikolajczak-etal-2026-team">
    <titleInfo>
        <title>Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Aygalic</namePart>
        <namePart type="family">Jara–Mikolajczak</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Thomas</namePart>
        <namePart type="family">Lavergne</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sophie</namePart>
        <namePart type="family">Rosset</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-10</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>The Proceedings of the Third Workshop on Uncertainty-Aware NLP</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Wilker</namePart>
            <namePart type="family">Aziz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Jonathan</namePart>
            <namePart type="family">Berant</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bryan</namePart>
            <namePart type="family">Eikema</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Evgenia</namePart>
            <namePart type="family">Ilia</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Marie-Catherine</namePart>
            <namePart type="family">de Marneffe</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Barbara</namePart>
            <namePart type="family">Plank</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Artem</namePart>
            <namePart type="family">Shelmanov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Swabha</namePart>
            <namePart type="family">Swayamdipta</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Jörg</namePart>
            <namePart type="family">Tiedemann</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Artem</namePart>
            <namePart type="family">Vazhentsev</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Raúl</namePart>
            <namePart type="family">Vázquez</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Chrysoula</namePart>
            <namePart type="family">Zerva</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Budapest, Hungary</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-486-6</identifier>
    </relatedItem>
    <abstract>We describe a multilingual, character-level hallucination detection system for vision-language models combining multi-layer hidden states, text-to-vision LoRA transfer, multitask learning, and language-specific span emission. Our submission achieved a validation Character AUPRC of 0.5530 and an average test Cor/Cor+lbl of 0.5243/0.4174. A controlled post-submission factorial analysis improved validation Character AUPRC to 0.5595. Team champ placed third in French, fourth in Italian and Chinese, and fifth in English.</abstract>
    <identifier type="citekey">jara-mikolajczak-etal-2026-team</identifier>
    <location>
        <url>https://aclanthology.org/2026.uncertainlp-main.62/</url>
    </location>
    <part>
        <date>2026-10</date>
        <extent unit="page">
            <start>856</start>
            <end>862</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation
%A Jara–Mikolajczak, Aygalic
%A Lavergne, Thomas
%A Rosset, Sophie
%Y Aziz, Wilker
%Y Berant, Jonathan
%Y Eikema, Bryan
%Y Ilia, Evgenia
%Y de Marneffe, Marie-Catherine
%Y Plank, Barbara
%Y Shelmanov, Artem
%Y Swayamdipta, Swabha
%Y Tiedemann, Jörg
%Y Vazhentsev, Artem
%Y Vázquez, Raúl
%Y Zerva, Chrysoula
%S The Proceedings of the Third Workshop on Uncertainty-Aware NLP
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-486-6
%F jara-mikolajczak-etal-2026-team
%X We describe a multilingual, character-level hallucination detection system for vision-language models combining multi-layer hidden states, text-to-vision LoRA transfer, multitask learning, and language-specific span emission. Our submission achieved a validation Character AUPRC of 0.5530 and an average test Cor/Cor+lbl of 0.5243/0.4174. A controlled post-submission factorial analysis improved validation Character AUPRC to 0.5595. Team champ placed third in French, fourth in Italian and Chinese, and fifth in English.
%U https://aclanthology.org/2026.uncertainlp-main.62/
%P 856-862

Download as File

Markdown (Informal)

[Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation](https://aclanthology.org/2026.uncertainlp-main.62/) (Jara–Mikolajczak et al., UncertaiNLP 2026)

Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation (Jara–Mikolajczak et al., UncertaiNLP 2026)

ACL

Aygalic Jara–Mikolajczak, Thomas Lavergne, and Sophie Rosset. 2026. Team champ at SHROOM-Visions: Transferring Fine-Grained Hallucination Detection with Hidden-State Probes and Backbone Adaptation. In The Proceedings of the Third Workshop on Uncertainty-Aware NLP, pages 856–862, Budapest, Hungary. Association for Computational Linguistics.