activity
20232026
most citedTowards Practical Federated Causal Structure Learning

13 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

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.SE2025

From Evaluation to Enhancement: Large Language Models for Zero-Knowledge Proof Code Generation

Zhantong Xue, Pingchuan Ma, Zhaoyu Wang +4

Zero-knowledge proofs (ZKPs) are increasingly deployed in domains such as privacy-preserving authentication, verifiable computation, and secure finance. However, authoring ZK progr…

cs.LG2023★ 13 cited

Towards Practical Federated Causal Structure Learning

Zhaoyu Wang, Pingchuan Ma, Shuai Wang

Understanding causal relations is vital in scientific discovery. The process of causal structure learning involves identifying causal graphs from observational data to understand s…