arXiv:2510. 06732v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small, natural-sounding prompts.
By Tiancheng Xing, Jerry Li, Yixuan Du, Xiyang Hu
arXiv:2607. 10252v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consumed through opaque serving chains - API aggregators, resellers, and inference providers - in which the client has no technical means to confirm that the model answering is the model advertised, and recent audits show that a substantial fraction of commercial endpoints deviate from the vendor's reference weights.
By Tomas Bruckner
The paper investigates the threat of stegomalware—malicious payloads hidden in large language model weights—and explores permutation symmetry as a defense. It demonstrates that carefully chosen permutations can neutralize stegomalware across all weights, unlike prior methods that left many weights untouched. Conversely, the same symmetry can be exploited to embed malware losslessly, without retraining or payload-specific extraction scripts, while only minimally affecting model performance.
By Danny Wood, James Stringer
arXiv:2603.17170v2 Announce Type: replace-cross
Abstract: AI agents increasingly execute users' natural-language (NL) tasks by calling Web services, yet today's Web authorizes these calls through OAu...
By Reshabh K Sharma, Linxi Jiang, Shuo Chen, Zhiqiang Lin
arXiv:2511. 00847v5 Announce Type: replace-cross Abstract: The widespread adoption of Large Language Models (LLMs) through Application Programming Interfaces (APIs) induces a critical vulnerability: the potential for dishonest manipulation by service providers.
By Yuhan Cao, Yu Wang, Sitong Liu, Miao Li, Yixin Tao, Tianxing He
arXiv:2609.24084v1 Announce Type: cross
Abstract: Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification di...
By Jiaxin Hong, Yuxin Peng, Hongyao Yu, Hao Fang, Shuoyang Sun, Bin Chen