新闻
Are These Programmers Ripe Enough to Eat? Evaluating How LLMs Handle Lexical Knowledge Conflicts in Translation
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers tested how nine LLMs handle conflicting word meanings in Mandarin-to-English translation when given new definitions via prompts.
- 为何重要
- Translation engineers and teams building multilingual systems need this when integrating external lexical resources that may contradict model training data.
- 注意
- Most models favor supplied meanings even when explicitly told to ignore them, and larger models within families rely more on conflicting definitions than smaller ones.
- llm
- language model
- prompt
- edge
- eval
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- Eval-Driven Development (Agent CI)
- MAPS: Multilingual Agent Performance & Security
- Temporal Knowledge Graph Memory
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