Multi Document Summarization

Multi-Document Summarization (MDS) is a crucial task in the field of natural language processing, aiming to condense multiple documents into a concise text by capturing key information and filtering out redundant content. This process primarily employs two methods: extractive and abstractive. The former extracts important segments directly from the original text, while the latter provides a generalized restatement of the document content, thereby achieving efficient information integration and communication.