Zero-Shot Cross-Lingual Summarization via Large Language Models

Understand

Given a document in a source language, cross-lingual summarization (CLS) aims to generate a summary in a different target language.

• Recently, the emergence of Large Language Models (LLMs), such as GPT-3.5, ChatGPT and GPT-4, has attracted wide attention from the computational linguistics community.
• However, it is not yet known the performance of LLMs on CLS.
• In this report, we empirically use various prompts to guide LLMs to perform zero-shot CLS from different paradigms (i.e., end-to-end and pipeline), and provide a preliminary evaluation on the generated summaries.