Papers by Jacob Hansen

1 papers
Self-Specialization: Uncovering Latent Expertise within Large Language Models (2024.findings-acl)

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Challenge: Recent studies have demonstrated the effectiveness of self-alignment in which a large language model is aligned to follow general instructions using instructional data generated from the model itself.
Approach: They propose to use human-written seeds to align large language models to follow general instructions to achieve cross-task generalization.
Outcome: The proposed model outperforms base models and models that are generally instruction-tuned or have been adapted to the target domain by a large margin.

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