activity
20242026
most citedDetect Llama -- Finding Vulnerabilities in Smart Contracts using Large Language Models

9 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

SoK: Cross-Chain Transaction Identification and Matching

Hang Zheng, Qishuang Fu, Joseph Liu +3

Cross-chain bridges, instant cryptocurrency exchanges, and centralized cross-ledger platforms move assets across an increasingly multi-chain ecosystem. However, these systems have…

cs.CR2026

FlowShield: cryptocurrency anti-money laundering with transaction semantics parsing and fund flow tracking

Qishuang Fu, Andreas Deppeler, Joseph K. Liu +5

Cryptocurrency anti-money laundering (Crypto AML) is increasingly challenged by sophisticated laundering behaviors that rapidly fragment stolen assets through diverse semantics and…

cs.CR2026

JUNO: Aggregated Vector Consensus for Optimal Asynchronous Common Subset

Liangrong Zhao, Qin Wang, Joseph K. Liu +1

In this paper, we propose \textit{aggregated vector consensus}, a new vector consensus primitive designed for asynchronous networks. The primitive achieves agreement by outputting…

cs.CR2025

Generative Large Language Model usage in Smart Contract Vulnerability Detection

Peter Ince, Jiangshan Yu, Joseph K. Liu +1

Recent years have seen an explosion of activity in Generative AI, specifically Large Language Models (LLMs), revolutionising applications across various fields. Smart contract vuln…

cs.CR20249 cited

Detect Llama -- Finding Vulnerabilities in Smart Contracts using Large Language Models

Peter Ince, Xiapu Luo, Jiangshan Yu +2

In this paper, we test the hypothesis that although OpenAI's GPT-4 performs well generally, we can fine-tune open-source models to outperform GPT-4 in smart contract vulnerability…