Papers by Hilla Merhav-Fine

1 papers
HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark (2023.findings-emnlp)

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Challenge: Current benchmarks for Hebrew Natural Language Processing (NLP) focus mainly on morpho-syntactic tasks, neglecting the semantic dimension of language understanding.
Approach: They propose to use Hebrew machine reading comprehension (MRC) as extractive Question Answering to address this problem.
Outcome: The proposed benchmark features 30,147 question-answer pairs derived from both Hebrew Wikipedia articles and Israeli tech news.

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