Summary of Multi-target Cross-lingual Summarization: a Novel Task and a Language-neutral Approach, by Diogo Pernes et al.
Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach
by Diogo Pernes, Gonçalo M. Correia, Afonso Mendes
First submitted to arxiv on: 1 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach is proposed for cross-lingual summarization, tackling the challenge of ensuring semantic coherence across different languages. Specifically, the task involves summarizing a document into multiple target languages while maintaining semantically similar summaries. The authors introduce a re-ranking approach to address this issue and develop a multi-criteria evaluation protocol to assess semantic coherence. This marks a significant step forward in this underexplored area, paving the way for further research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Cross-lingual summarization is a big deal because it can help people understand documents written in different languages. The problem is that making sure the summaries are accurate and make sense across languages is really hard. To solve this, scientists came up with a new way to summarize documents into multiple languages while keeping the same meaning. They also created a way to measure how well their method works. This breakthrough has the potential to improve communication between people who speak different languages. |
Keywords
» Artificial intelligence » Summarization
