Papers with paragraph-to-paragraph comparison

1 papers
Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models (2024.emnlp-industry)

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Challenge: Existing methods for evaluating the quality and consistency of text generated by Large Language Models are not effective.
Approach: They propose a divide-conquer-reasoning approach to evaluate LLM-generated texts using a split-and-conquers evaluator and an automatic metric converter to facilitate this approach.
Outcome: The proposed framework outperforms state-of-the-art methods by a large margin on multiple benchmarks and reduces 90% of output inconsistencies in one iteration.

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