R0027/2026-03-26/Q001/S01/R01¶
Comprehensive survey of multilingual prompt engineering techniques across NLP tasks
Summary¶
| Field | Value |
|---|---|
| Title | Multilingual Prompt Engineering in Large Language Models: A Survey Across NLP Tasks |
| URL | https://arxiv.org/abs/2505.11665 |
| Date accessed | 2026-03-26 |
| Publication date | 2025-05-16 |
| Author(s) | Shubham Vatsal, Harsh Dubey, Aditi Singh |
| Publication | arXiv preprint |
Selection Decision¶
Included in evidence base: Yes
Rationale: Most comprehensive survey found — covers 36 papers, 39 prompting techniques, 30 NLP tasks, ~250 languages. Directly addresses the query about cross-language prompt engineering effectiveness.