13 citations · 16 across the 28 of their papers we have counts for
9 papers · 1 filter
MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification
Xu-Yang Chen, Lu Han, De-Chuan Zhan +1
Network traffic includes data transmitted across a network, such as web browsing and file transfers, and is organized into packets (small units of data) and flows (sequences of pac…
OmniEvalKit: A Modular, Lightweight Toolbox for Evaluating Large Language Model and its Omni-Extensions
Yi-Kai Zhang, Xu-Xiang Zhong, Shiyin Lu +3
The rapid advancements in Large Language Models (LLMs) have significantly expanded their applications, ranging from multilingual support to domain-specific tasks and multimodal int…
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao +3
Class-Incremental Learning (CIL) requires models to continually acquire knowledge of new classes without forgetting old ones. Despite Pre-trained Models (PTMs) have shown excellent…
Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning
Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye +2
Domain-Incremental Learning (DIL) involves the progressive adaptation of a model to new concepts across different domains. While recent advances in pre-trained models provide a sol…
Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning
Zhi-Hong Qi, Da-Wei Zhou, Yiran Yao +2
In our ever-evolving world, new data exhibits a long-tailed distribution, such as e-commerce platform reviews. This necessitates continuous model learning imbalanced data without f…
Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks
Yichu Xu, Xin-Chun Li, Lan Li +1
The loss landscape of deep neural networks (DNNs) is commonly considered complex and wildly fluctuated. However, an interesting observation is that the loss surfaces plotted along…
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
Xin-Chun Li, Jin-Lin Tang, Bo Zhang +2
Exploring the loss landscape offers insights into the inherent principles of deep neural networks (DNNs). Recent work suggests an additional asymmetry of the valley beyond the flat…
Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification
Chao Yi, Lu Ren, De-Chuan Zhan +1
CLIP showcases exceptional cross-modal matching capabilities due to its training on image-text contrastive learning tasks. However, without specific optimization for unimodal scena…
SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
Lu Han, Xu-Yang Chen, Han-Jia Ye +1
Multivariate time series forecasting plays a crucial role in various fields such as finance, traffic management, energy, and healthcare. Recent studies have highlighted the advanta…