Xiaoqi Li

LibScan is an automated framework that detects eight categories of smart contract library misuse by combining LLM-based semantic reasoning with rule-based analysis, achieving 85.15% accuracy on real-world contracts.

LiquiLM is a novel framework that combines Large Language Models (LLMs) with a Dynamic Co-Attention Network (DCN) to effectively bridge the semantic gap between complex smart contract code and high-level liquidity flaw descriptions, achieving high accuracy in auditing DeFi systems.

The paper introduces PSR extsuperscript{2}, a novel static analysis framework that significantly improves the detection of atomicity violations in smart contracts by combining structural path searching with deep semantic reasoning.

NFTDELTA is a novel framework that uses multi-view learning on static code analysis to detect permission control vulnerabilities in NFT contracts with high accuracy.

This paper proposes ShopX, a model-centric framework for intent-driven shopping experiences using a single foundation model for intent understanding, execution planning, and item-space operations.