A Dutch BERT model encodes gender linearly by epoch 20 but does not dynamically update its representations when explicit female cues contradict learned stereotypical associations in short sentence templates.
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LLMs show scaling and training-dependent alignment with human brain responses in creativity-related networks during divergent thinking tasks, measured via RSA on fMRI data.
MIPIC trains nested Matryoshka representations via self-distilled intra-relational alignment with top-k CKA and progressive information chaining across depths, yielding competitive performance especially at extreme low dimensions.
citing papers explorer
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Is She Even Relevant? When BERT Ignores Explicit Gender Cues
A Dutch BERT model encodes gender linearly by epoch 20 but does not dynamically update its representations when explicit female cues contradict learned stereotypical associations in short sentence templates.
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Large Language Models Align with the Human Brain during Creative Thinking
LLMs show scaling and training-dependent alignment with human brain responses in creativity-related networks during divergent thinking tasks, measured via RSA on fMRI data.
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MIPIC: Matryoshka Representation Learning via Self-Distilled Intra-Relational and Progressive Information Chaining
MIPIC trains nested Matryoshka representations via self-distilled intra-relational alignment with top-k CKA and progressive information chaining across depths, yielding competitive performance especially at extreme low dimensions.
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