Papers with Google search engine

2 papers
GooAQ: Open Question Answering with Diverse Answer Types (2021.findings-emnlp)

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Challenge: Existing research on niche answer types, mainly short responses and, in a few cases, long responses, has failed to adequately address the answer diversity of questions.
Approach: They propose to use Google's autocomplete feature to collect questions from a large-scale dataset with a variety of answer types to facilitate further research on improving QA with diverse response types.
Outcome: The proposed model produces naturalistic questions that are short and expressed using simple language.
MCECR: A Novel Dataset for Multilingual Cross-Document Event Coreference Resolution (2024.findings-naacl)

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Challenge: Existing datasets for event coreference resolution focus on within-document event coreference and English text, lacking cross-document ECR datasets beyond English.
Approach: They propose a multiligual dataset that manually annotates documents for event mentions and coreference in five languages.
Outcome: The proposed dataset annotates documents for event mentions and coreference in five languages . the dataset fetches related news articles from the google search engine to increase the number of non-singleton clusters .

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