306 citations · 313 across the 6 of their papers we have counts for
5 papers
Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning
Chongyang Tao, Jiazhan Feng, Chang Liu +3
Establishing retrieval-based dialogue systems that can select appropriate responses from the pre-built index has gained increasing attention from researchers. For this task, the ad…
R-Drop: Regularized Dropout for Neural Networks
Xiaobo Liang, Lijun Wu, Juntao Li +6
Dropout is a powerful and widely used technique to regularize the training of deep neural networks. In this paper, we introduce a simple regularization strategy upon dropout in mod…
Dialogue History Matters! Personalized Response Selectionin Multi-turn Retrieval-based Chatbots
Juntao Li, Chang Liu, Chongyang Tao +4
Existing multi-turn context-response matching methods mainly concentrate on obtaining multi-level and multi-dimension representations and better interactions between context uttera…
Feature Adaptation of Pre-Trained Language Models across Languages and Domains with Robust Self-Training
Hai Ye, Qingyu Tan, Ruidan He +3
Adapting pre-trained language models (PrLMs) (e.g., BERT) to new domains has gained much attention recently. Instead of fine-tuning PrLMs as done in most previous work, we investig…
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce
Juntao Li, Chang Liu, Jian Wang +5
With the prosperous of cross-border e-commerce, there is an urgent demand for designing intelligent approaches for assisting e-commerce sellers to offer local products for consumer…