Search Results for author: Di Cao

Found 7 papers, 1 papers with code

RealVul: Can We Detect Vulnerabilities in Web Applications with LLM?

no code implementations10 Oct 2024 Di Cao, Yong Liao, Xiuwei Shang

The latest advancements in large language models (LLMs) have sparked interest in their potential for software vulnerability detection.

Vulnerability Detection

EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection

1 code implementation27 Jul 2024 Shigang Liu, Di Cao, Junae Kim, Tamas Abraham, Paul Montague, Seyit Camtepe, Jun Zhang, Yang Xiang

Recently, deep learning has demonstrated promising results in enhancing the accuracy of vulnerability detection and identifying vulnerabilities in software.

Adversarial Attack Vulnerability Detection

LightCAM: A Fast and Light Implementation of Context-Aware Masking based D-TDNN for Speaker Verification

no code implementations8 Feb 2024 Di Cao, Xianchen Wang, Junfeng Zhou, Jiakai Zhang, Yanjing Lei, Wenpeng Chen

Traditional Time Delay Neural Networks (TDNN) have achieved state-of-the-art performance at the cost of high computational complexity and slower inference speed, making them difficult to implement in an industrial environment.

Speaker Verification

Model-Free Voltage Regulation of Unbalanced Distribution Network Based on Surrogate Model and Deep Reinforcement Learning

no code implementations24 Jun 2020 Di Cao, Junbo Zhao, Weihao Hu, Fei Ding, Qi Huang, Zhe Chen, Frede Blaabjerg

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage controls, but this is difficult to obtain in practice.

Decision Making Deep Reinforcement Learning +1

Distributed Voltage Regulation of Active Distribution System Based on Enhanced Multi-agent Deep Reinforcement Learning

no code implementations31 May 2020 Di Cao, Junbo Zhao, Weihao Hu, Fei Ding, Qi Huang, Zhe Chen

This paper proposes a data-driven distributed voltage control approach based on the spectrum clustering and the enhanced multi-agent deep reinforcement learning (MADRL) algorithm.

Clustering Deep Reinforcement Learning

Binarized LSTM Language Model

no code implementations NAACL 2018 Xuan Liu, Di Cao, Kai Yu

Although excellent performance is obtained for large vocabulary tasks, tremendous memory consumption prohibits the use of LSTM LM in low-resource devices.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

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