collaborators

7 papers

cs.CR2026

Sound Debloating of Redundant Checks in Zero-Knowledge Machine-Learning Circuits

Zhantong Xue, Pingchuan Ma, Zhaoyu Wang +3

Zero-knowledge (ZK) proof systems for neural-network inference compile the model into a system of arithmetic constraints. Many of these constraints are redundant checks: range proo…

cs.SE2026

AutoSpec: Safety Rule Evolution for LLM Agents via Inductive Logic Programming

Pingchuan Ma, Zhaoyu Wang, Zimo Ji +5

Large language model (LLM) agents increasingly automate complex tasks by integrating language models with external tools and environments. However, their autonomy poses significant…

cs.CR2026

From Shield to Target: Denial-of-Service Attacks on LLM-Based Agent Guardrails

Yuguang Zhou, Xunguang Wang, Pingchuan Ma +3

LLM-based guardrails have emerged as a highly effective defense against prompt injection and jailbreak attacks in autonomous agents. However, we reveal that the very reasoning and…

cs.CR2026

ZK-Value: A Practical Zero-Knowledge System for Verifiable Data Valuation

Zhaoyu Wang, Pingchuan Ma, Zhantong Xue +4

Data valuation is a foundational task in data marketplaces, where a Shapley-value attribution determines how a buyer's payment is distributed among data providers. Typically, the m…

cs.AI2026

Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models

Xunguang Wang, Yuguang Zhou, Qingyue Wang +5

Large language models increasingly rely on explicit chain-of-thought reasoning to solve complex tasks, yet the safety of the reasoning process itself remains largely unaddressed. E…

cs.CR2025

RepoMark: A Data-Usage Auditing Framework for Code Large Language Models

Wenjie Qu, Yuguang Zhou, Bo Wang +4

The rapid development of Large Language Models (LLMs) for code generation has transformed software development by automating coding tasks with unprecedented efficiency. However, th…