3 citations · 3 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
Large Language Models Reasoning Abilities Under Non-Ideal Conditions After RL-Fine-Tuning
Chang Tian, Matthew B. Blaschko, Mingzhe Xing +3
Reinforcement learning (RL) has become a key technique for enhancing the reasoning abilities of large language models (LLMs), with policy-gradient algorithms dominating the post-tr…
OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine
Jie Ma, Ningyu He, Jinwen Xi +4
As Ethereum continues to thrive, the Ethereum Virtual Machine (EVM) has become the cornerstone powering tens of millions of active smart contracts. Intuitively, security issues in…
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…