Papers by Lotem Golany

1 papers
Efficient Data Generation for Source-grounded Information-seeking Dialogs: A Use Case for Meeting Transcripts (2024.findings-emnlp)

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Challenge: Existing methods for automating data generation with Large Language Models (LLMs) are difficult, and we propose a semi-automatic approach to generate dialogs with attributions.
Approach: They propose a semi-automatic approach to generate dialog queries and responses with Large Language Models followed by human verification and identification of attribution spans.
Outcome: The proposed approach improves the quality of the response generation and attribution quality of MISeD datasets while reducing time and effort.

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