Papers by Neslihan Iskender

2 papers
Does Summary Evaluation Survive Translation to Other Languages? (2022.naacl-main)

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Challenge: a quality summarization dataset requires the production and evaluation of summaries by trained humans and machines.
Approach: They translate a summarization dataset in English and compare its performance to seven languages . they explore equivalence testing as an appropriate statistical paradigm for evaluating correlations between human and automated scoring of summaries .
Outcome: The proposed method could be used in seven languages and compares performance across measures.
Towards a Reliable and Robust Methodology for Crowd-Based Subjective Quality Assessment of Query-Based Extractive Text Summarization (2020.lrec-1)

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Challenge: a growing number of documents are needed for multi-document summarization.
Approach: They propose crowdsourcing to evaluate intrinsic and extrinsic quality of extractive text summaries . they conduct intensive comparative crowdsourcing and laboratory experiments .
Outcome: The proposed crowdsourcing task evaluates intrinsic and extrinsic quality of extractive text summaries.

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