SkinGEN: an Explainable Dermatology Diagnosis-to-Generation Framework with Interactive Vision-Language Models

no code implementations • 23 Apr 2024 • Bo Lin, Yingjing Xu, Xuanwen Bao, Zhou Zhao, Zuyong Zhang, Zhouyang Wang, Jie Zhang, Shuiguang Deng, Jianwei Yin

With the continuous advancement of vision language models (VLMs) technology, remarkable research achievements have emerged in the dermatology field, the fourth most prevalent human disease category.

Hallucination Image Generation

GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing

2 code implementations • 9 Mar 2024 • Hao Lu, Xuesong Niu, Jiyao Wang, Yin Wang, Qingyong Hu, Jiaqi Tang, Yuting Zhang, Kaishen Yuan, Bin Huang, Zitong Yu, Dengbo He, Shuiguang Deng, Hao Chen, Yingcong Chen, Shiguang Shan

In conclusion, this paper provides valuable insights into the potential applications and challenges of MLLMs in human-centric computing.

Emotion Recognition Facial Action Unit Detection +4

Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes

2 code implementations • 11 Dec 2023 • Zhen Qin, Daoyuan Chen, Bingchen Qian, Bolin Ding, Yaliang Li, Shuiguang Deng

Pre-trained large language models (LLMs) need fine-tuning to improve their responsiveness to natural language instructions.

Federated Learning Large Language Model

Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection

no code implementations • 26 Nov 2023 • Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng

Anomaly detection significantly enhances the robustness of cloud systems.

Anomaly Detection Time Series +1

CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation

1 code implementation • 14 Nov 2023 • Weixiang Yan, Haitian Liu, Yunkun Wang, Yunzhe Li, Qian Chen, Wen Wang, Tingyu Lin, Weishan Zhao, Li Zhu, Shuiguang Deng, Hari Sundaram

To bridge these gaps between existing benchmarks and expectations from practical applications, we introduce CodeScope, an execution-based, multilingual, multi-task, multi-dimensional evaluation benchmark for comprehensively gauging LLM capabilities on coding tasks.

Code Generation

LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection

no code implementations • 9 Oct 2023 • Feiyi Chen, Zhen Qin, Yingying Zhang, Shuiguang Deng, Yi Xiao, Guansong Pang, Qingsong Wen

Retraining a large neural network model with limited data is vulnerable to overfitting.

Time Series Time Series Anomaly Detection +1

Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective

1 code implementation • 28 Sep 2023 • Zhen Qin, Feiyi Chen, Chen Zhi, Xueqiang Yan, Shuiguang Deng

Existing approaches defend against backdoor attacks in federated learning (FL) mainly through a) mitigating the impact of infected models, or b) excluding infected models.

Federated Learning

PePNet: A Periodicity-Perceived Workload Prediction Network Supporting Rare Occurrence of Heavy Workload

no code implementations • 11 Jul 2023 • Feiyi Chen, Zhen Qin, Hailiang Zhao, Mengchu Zhou, Shuiguang Deng

This impairs the prediction accuracy of neural network-based models on heavy workload.

Cyclic Arbitrage in Decentralized Exchanges

no code implementations • 21 Apr 2021 • Ye Wang, Yan Chen, Haotian Wu, Liyi Zhou, Shuiguang Deng, Roger Wattenhofer

We find that traders have executed 292, 606 cyclic arbitrages over eleven months and exploited more than 138 million USD in revenue.