[Submitted on 17 Mar 2026 (
), last revised 13 Apr 2026 (this version, v3)]
Title:Resource Consumption Threats in Large Language Models
Authors:Yuanhe Zhang
,
,
,
,
,
,
,
,
,
,
View a PDF of the paper titled Resource Consumption Threats in Large Language Models, by Yuanhe Zhang and 10 other authors
Abstract:Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LLMs increase service capacity for providers and reduce latency and API costs for users. Recent resource consumption threats induce excessive generation, degrading model efficiency and harming both service availability and economic sustainability. This survey presents a systematic review of threats to resource consumption in LLMs. We further establish a unified view of this emerging area by clarifying its scope and examining the problem along the full pipeline from threat induction to mechanism understanding and mitigation. Our goal is to clarify the problem landscape for this emerging area, thereby providing a clearer foundation for characterization and mitigation.
Submission history
From: Yuanhe Zhang [
]
Tue, 17 Mar 2026 02:35:04 UTC (2,700 KB)
Wed, 18 Mar 2026 01:51:39 UTC (2,700 KB)
[v3]
Mon, 13 Apr 2026 03:47:48 UTC (2,685 KB)