Efficiently and Effectively: A Two-stage Approach to Balance Plaintext and Encrypted Text for Traffic Classification

no code implementations • 29 Jul 2024 • Wei Peng, Lei Cui, Wei Cai, Zhenquan Ding, Zhiyu Hao, Xiaochun Yun

In this paper, for the first time, we analyze the impact of plaintext and encrypted text on the model's effectiveness and efficiency.

Classification Traffic Classification

Hybrid Multi-stage Decoding for Few-shot NER with Entity-aware Contrastive Learning

no code implementations • 10 Apr 2024 • Peipei Liu, Gaosheng Wang, Ying Tong, Jian Liang, Zhenquan Ding, Hongsong Zhu

In the training process, we train and get the best entity-span detection model and the entity classification model separately on the source domain using meta-learning, where we create a contrastive learning module to enhance entity representations for entity classification.

Classification Contrastive Learning +7