Papers by Yongbing Zhang

1 papers
A Mixed-Language Multi-Document News Summarization Dataset and a Graphs-Based Extract-Generate Model (2025.naacl-long)

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Challenge: Existing research on news summarization focuses on single-language single-document (SLSD), single-linguistic multi-document or cross-language multi-doc (CLSD) however, in real-world scenarios, news articles often involve multiple documents in different languages, i.e., mixed-language MLMD.
Approach: They propose a mixed-language multi-document news summarization dataset with four different languages and 10,992 source document cluster and target summary pairs.
Outcome: The proposed dataset contains four different languages and 10,992 source document cluster and target summary pairs.

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