Papers by Kuleen Sasse

2 papers
Making FETCH! Happen: Finding Emergent Dog Whistles Through Common Habitats (2025.acl-long)

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Challenge: Dog whistles are coded expressions with dual meanings that slip by content moderation filters . a new study finds that state-of-the-art systems fail to identify novel dog whistles .
Approach: They propose a task to find novel dog whistles in massive social media corpora . they use a strong baseline system that combines vector databases and Large Language Models to identify new dog whistle.
Outcome: The proposed system fails to identify dog whistles across three social media cases . it combines vector databases and Large Language Models to efficiently and effectively identify new dog whistle expressions.
Sparse Autoencoder Features for Classifications and Transferability (2025.emnlp-main)

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Challenge: Sparse Autoencoders (SAEs) provide potential for uncovering structured, human-interpretable representations in Large Language Models (LLMs).
Approach: They analyze SAEs for interpretable feature extraction from Large Language Models in safety-critical classification tasks.
Outcome: The proposed framework outperforms hidden-state and BoW models while demonstrating cross-lingual toxicity detection and visual classification tasks.

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