Papers by Artem Harutyunyan

1 papers
BYOC: Personalized Few-Shot Classification with Co-Authored Class Descriptions (2023.findings-emnlp)

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Challenge: Existing approaches to text classification require large annotated corpora to train or long context to fit many examples.
Approach: They propose a method to few-shot text classification using an LLM.
Outcome: The proposed approach yields high accuracy classifiers within 79% of the performance of models trained with larger datasets while using only 1% of their training sets.

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