9 papers
Binary Decompilation LLM with Feedback-Driven Multi-Turn Refinement
Peipei Liu, Jian Sun, Mingzhe Xing +5
Binary decompilation is fundamental to security tasks such as vulnerability discovery, malware inspection, and executable-only program understanding. Recent LLM-based decompilation…
NEXUS: Continual Learning of Symbolic Constraints for Safe and Robust Embodied Planning
Tiehan Cui, Peipei Liu, Yanxu Mao +3
While Large Language Models (LLMs) have catalyzed progress in embodied intelligence, a fundamental gap between their inherent probabilistic uncertainty and the strict determinism a…
Stop Fixating on Prompts: Reasoning Hijacking and Constraint Tightening for Red-Teaming LLM Agents
Yanxu Mao, Peipei Liu, Tiehan Cui +3
With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team methods mostly rely on modifying…
When Specifications Meet Reality: Uncovering API Inconsistencies in Ethereum Infrastructure
Jie Ma, Ningyu He, Jinwen Xi +8
The Ethereum ecosystem, which secures over $381 billion in assets, fundamentally relies on client APIs as the sole interface between users and the blockchain. However, these critic…
Understanding Network Behaviors through Natural Language Question-Answering
Mingzhe Xing, Chang Tian, Jianan Zhang +4
Modern large-scale networks introduce significant complexity in understanding network behaviors, increasing the risk of misconfiguration. Prior work proposed to understand network…
Using Causality for Enhanced Prediction of Web Traffic Time Series
Chang Tian, Mingzhe Xing, Zenglin Shi +3
Predicting web service traffic has significant social value, as it can be applied to various practical scenarios, including but not limited to dynamic resource scaling, load balanc…