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Atyaephyra at SemEval-2025 Task 4: Low-Rank Negative Preference Optimization

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10511573" target="_blank" >RIV/00216208:11320/25:10511573 - isvavai.cz</a>

  • Result on the web

    <a href="https://aclanthology.org/2025.semeval-1.187/" target="_blank" >https://aclanthology.org/2025.semeval-1.187/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Atyaephyra at SemEval-2025 Task 4: Low-Rank Negative Preference Optimization

  • Original language description

    We present a submission to the SemEval 2025 shared task on unlearning sensitive content from LLMs. Our approach employs negative preference optimization using low-rank adaptation. We show that we can utilize this combination to efficiently compute additional regularization terms, which help with unlearning stabilization. The results of our approach significantly exceed the shared task baselines.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EH23_025%2F0008691" target="_blank" >EH23_025/0008691: Human-centred AI for a Sustainable and Adaptive Society</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)

  • ISBN

    979-8-89176-273-2

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    1415-1422

  • Publisher name

    Association for Computational Lingustics

  • Place of publication

    Kerrville, TX, USA

  • Event location

    Wien, Austria

  • Event date

    Jul 31, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article