Papers with automatic factuality metrics

2 papers
Controllable Factuality in Document-Grounded Dialog Systems Using a Noisy Channel Model (2022.findings-emnlp)

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Challenge: Recent document-grounded dialog systems have seen an increase in popularity.
Approach: They propose a model for document-grounded response generation in dialog that is decomposed into two components according to Bayes’ theorem and propose different approximate decoding schemes.
Outcome: The proposed model is more factual in terms of automatic factuality metrics than the baseline model and can be combined with a recently proposed method to control factuity in grounded dialog, CTRL.
LongDocFACTScore: Evaluating the Factuality of Long Document Abstractive Summarisation (2024.lrec-main)

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Challenge: Existing metrics for text summarisation have restrictive token limits, limiting their effectiveness.
Approach: They propose a human-annotated data set for evaluating automatic factuality metrics . they propose 'longDocFACTScore' framework which can be extended to any length document .
Outcome: The proposed framework outperforms state-of-the-art metrics in evaluating long document summarisation data sets.

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