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LLM Trojans that Increase Response Lengths and Cost
ZL

Zhengxing Li, Guangmingmei Yang, Nader Alfares, David J. Miller, George Kesidis

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ResearcharXiv cs.AI

LLM Trojans that Increase Response Lengths and Cost

arXiv:2610.24784v1 Announce Type: cross Abstract: Management of the token-based costs of using LLMs has emerged as a significant problem. Some frontier-model providers charge five times per response token than per prompt token, while others offer prefilling discounts for prompt tokens. In this paper, we devise a defense against a new data-poisoning attack that plants a Trojan which increases the length of the response (and hence the cost to the user) when its trigger is present in the prompt. In particular, we demonstrate how a subtle Trojan may trigger on semantically similar instructions of an instruction fine-tuned LLM.

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This story was published by arXiv cs.AI and written by Zhengxing Li, Guangmingmei Yang, Nader Alfares, David J. Miller, George Kesidis. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on arxiv.org

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