Scaling Behavior of Machine Translation with Large Language Models under Prompt Injection Attacks

Zhifan Sun, Antonio Valerio Miceli-Barone


Abstract
Large Language Models (LLMs) are increasingly becoming the preferred foundation platforms for many Natural Language Processing tasks such as Machine Translation, owing to their quality often comparable to or better than task-specific models, and the simplicity of specifying the task through natural language instructions or in-context examples.Their generality, however, opens them up to subversion by end users who may embed into their requests instructions that cause the model to behave in unauthorized and possibly unsafe ways.In this work we study these Prompt Injection Attacks (PIAs) on multiple families of LLMs on a Machine Translation task, focusing on the effects of model size on the attack success rates.We introduce a new benchmark data set and we discover that on multiple language pairs and injected prompts written in English, larger models under certain conditions may become more susceptible to successful attacks, an instance of the Inverse Scaling phenomenon (McKenzie et al., 2023).To our knowledge, this is the first work to study non-trivial LLM scaling behaviour in a multi-lingual setting.
Anthology ID:
2024.scalellm-1.2
Volume:
Proceedings of the First edition of the Workshop on the Scaling Behavior of Large Language Models (SCALE-LLM 2024)
Month:
March
Year:
2024
Address:
St. Julian’s, Malta
Editors:
Antonio Valerio Miceli-Barone, Fazl Barez, Shay Cohen, Elena Voita, Ulrich Germann, Michal Lukasik
Venues:
SCALE-LLM | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
9–23
Language:
URL:
https://aclanthology.org/2024.scalellm-1.2
DOI:
Bibkey:
Cite (ACL):
Zhifan Sun and Antonio Valerio Miceli-Barone. 2024. Scaling Behavior of Machine Translation with Large Language Models under Prompt Injection Attacks. In Proceedings of the First edition of the Workshop on the Scaling Behavior of Large Language Models (SCALE-LLM 2024), pages 9–23, St. Julian’s, Malta. Association for Computational Linguistics.
Cite (Informal):
Scaling Behavior of Machine Translation with Large Language Models under Prompt Injection Attacks (Sun & Miceli-Barone, SCALE-LLM-WS 2024)
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PDF:
https://aclanthology.org/2024.scalellm-1.2.pdf