Papers by Yann Choho

    1 papers
    Towards Achieving Concept Completeness for Textual Concept Bottleneck Models (2025.findings-emnlp)

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    Challenge: a novel TCBM generator is proposed to build concept labels in unsupervised manner using a small language model.
    Approach: They propose a complete textual concept bottleneck model that builds concept labels in unsupervised manner using a small language model.
    Outcome: The proposed model achieves striking results against existing models in terms of concept basis completeness and concept detection accuracy.

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