3 papers
cs.CR2026
Progent: Securing AI Agents with Privilege Control
Tianneng Shi, Jingxuan He, Zhun Wang +4
AI agents interact with external environments through tool calls, exposing them to attacks like indirect prompt injection that can trigger unauthorized actions. Securing these agen…
cs.CR2026
IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation
Yanpei Guo, Wenjie Qu, Linyu Wu +7
Commercial large language models are typically deployed as black-box API services, requiring users to trust providers to execute inference correctly and report token usage honestly…
cs.DC2025
DeServe: Towards Affordable Offline LLM Inference via Decentralization
Linyu Wu, Xiaoyuan Liu, Tianneng Shi +2
The rapid growth of generative AI and its integration into everyday workflows have significantly increased the demand for large language model (LLM) inference services. While propr…