Papers by Atabak Ashfaq

2 papers
Re-evaluating Evaluation in Text Summarization (2020.emnlp-main)

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Challenge: Automated evaluation metrics are an essential part of the development of text-generation tasks such as summarization.
Approach: They propose to use top-scoring system outputs to assess the reliability of automatic evaluation metrics for text summarization.
Outcome: The proposed evaluation method is based on human judgments from 25 top-scoring neural summarization systems.
Metrics also Disagree in the Low Scoring Range: Revisiting Summarization Evaluation Metrics (2020.coling-main)

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Challenge: In text summarization evaluation, evaluating the efficacy of automated metrics without human judgments has become popular.
Approach: They revisit their experiments and find that automatic metrics disagree when ranking high-scoring summaries.
Outcome: The proposed method is a human judgment-free method, but it is not a meta-evaluation strategy.

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