IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation
National University of Singapore（新加坡国立大学）；Nanyang Technological University（南洋理工大学）；Independent Researcher（独立研究者）；University of California, Berkeley（加州大学伯克利分校）
Yanpei Guo, Wenjie Qu, Linyu Wu, Shengfang Zhai, Lionel Z. Wang, Ming Xu, Yue Liu, Binhang Yuan, Dawn Song, Jiaheng Zhang
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. We present IMMACULATE, a practical auditing framework that detects economically motivated deviations-such as model substitution, quantization abuse, and token overbilling-without trusted hardware or access to model internals. IMMACULATE selectively audits a small fraction of requests using verifiable computation, achieving strong detection guarantees while amortizing cryptographic overhead. Experiments on dense and MoE models show that IMMACULATE reliably distinguishes benign and malicious executions with under 1% throughput overhead. Our code is published at https://github.com/guo-yanpei/Immaculate.
organization= Huazhong University of Science；organization= Lingnan University；organization= Centre for Artificial Intelligence；Robotics (CAIR) Hong Kong Institute of Science \& Innovation, Chinese Academy of Sciences；Tsinghua University；Fujian Jiangxia University
Auditing Data Membership in Reinforcement Learning With Verifiable Rewards
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Shanghai Jiao Tong University（上海交通大学）；Shandong University（山东大学）；Xidian University（西安电子科技大学）；Wuhan University（武汉大学）
vCause: Efficient and Verifiable Causality Analysis for Cloud-based Endpoint Auditing
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）；University of Electronic Science and Technology of China（电子科技大学）；Qi An Xin Technology Group Inc.（奇安信科技集团股份有限公司）
QUACK: Questioning, Understanding, and Auditing Communicated Knowledge in Multimodal Social Deduction Agents
McGill University（麦吉尔大学）；Mila - Quebec AI Institute（魁北克人工智能研究所）；University of Cambridge（剑桥大学）；MBZUAI - Mohamed bin Zayed University of Artificial Intelligence（MBZUAI - 摩苏尔·本·扎耶德人工智能大学）；University of Toronto（多伦多大学）；Salesforce
PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generation
Singapore Management University（新加坡管理大学）；MetaTrust Labs（MetaTrust实验室）；The Hong Kong University of Science and Technology（香港科技大学）；Nanyang Technological University（南洋理工大学）；China-Singapore International Joint Research Institute (CSIJRI)（中新国际联合研究院（CSIJRI））
DHMark: Public-Key Watermarking for LLM-Generated Text via Diffie-Hellman-Guided Rejection Sampling
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）
