54 citations · 95 across the 15 of their papers we have counts for
16 papers
PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning
Huiwei Lin, Baoquan Zhang, Shanshan Feng +2
Online class-incremental continual learning is a specific task of continual learning. It aims to continuously learn new classes from data stream and the samples of data stream are…
Gated Mechanism Enhanced Multi-Task Learning for Dialog Routing
Ziming Huang, Zhuoxuan Jiang, Ke Wang +3
Currently, human-bot symbiosis dialog systems, e.g., pre- and after-sales in E-commerce, are ubiquitous, and the dialog routing component is essential to improve the overall effici…
Leveraging Key Information Modeling to Improve Less-Data Constrained News Headline Generation via Duality Fine-Tuning
Zhuoxuan Jiang, Lingfeng Qiao, Di Yin +2
Recent language generative models are mostly trained on large-scale datasets, while in some real scenarios, the training datasets are often expensive to obtain and would be small-s…
MetaDT: Meta Decision Tree with Class Hierarchy for Interpretable Few-Shot Learning
Baoquan Zhang, Hao Jiang, Xutao Li +3
Few-Shot Learning (FSL) is a challenging task, which aims to recognize novel classes with few examples. Recently, lots of methods have been proposed from the perspective of meta-le…
Enhancing Hyperbolic Graph Embeddings via Contrastive Learning
Jiahong Liu, Menglin Yang, Min Zhou +2
Recently, hyperbolic space has risen as a promising alternative for semi-supervised graph representation learning. Many efforts have been made to design hyperbolic versions of neur…
SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification
Baoquan Zhang, Shanshan Feng, Xutao Li +2
Few-Shot Remote Sensing Scene Classification (FSRSSC) is an important task, which aims to recognize novel scene classes with few examples. Recently, several studies attempt to addr…
RAP-Net: Region Attention Predictive Network for Precipitation Nowcasting
Chuyao Luo, ZhengZhang, Rui Ye +2
Natural disasters caused by heavy rainfall often cost huge loss of life and property. To avoid it, the task of precipitation nowcasting is imminent. To solve the problem, increasin…
Prototype Completion for Few-Shot Learning
Baoquan Zhang, Xutao Li, Yunming Ye +1
Few-shot learning aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a feature extractor and then fine-tun…
Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation
Sanshi Yu, Zhuoxuan Jiang, Dong-Dong Chen +4
Recently, a new form of online shopping becomes more and more popular, which combines live streaming with E-Commerce activity. The streamers introduce products and interact with th…
Exploiting Global Contextual Information for Document-level Named Entity Recognition
Zanbo Wang, Wei Wei, Xianling Mao +4
Most existing named entity recognition (NER) approaches are based on sequence labeling models, which focus on capturing the local context dependencies. However, the way of taking o…
MetaNODE: Prototype Optimization as a Neural ODE for Few-Shot Learning
Baoquan Zhang, Xutao Li, Shanshan Feng +2
Few-Shot Learning (FSL) is a challenging task, \emph{i.e.}, how to recognize novel classes with few examples? Pre-training based methods effectively tackle the problem by pre-train…
Exploiting Group-level Behavior Pattern forSession-based Recommendation
Ziyang Wang, Wei Wei, Xian-Ling Mao +2
Session-based recommendation (SBR) is a challenging task, which aims to predict users' future interests based on anonymous behavior sequences. Existing methods leverage powerful re…
User-based Network Embedding for Collective Opinion Spammer Detection
Ziyang Wang, Wei Wei, Xian-Ling Mao +3
Due to the huge commercial interests behind online reviews, a tremendousamount of spammers manufacture spam reviews for product reputation manipulation. To further enhance the infl…
A Survey on Recent Advances in Sequence Labeling from Deep Learning Models
Zhiyong He, Zanbo Wang, Wei Wei +3
Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks, e.g., part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc. Th…
Exploring Global Information for Session-based Recommendation
Ziyang Wang, Wei Wei, Gao Cong +4
Session-based recommendation (SBR) is a challenging task, which aims at recommending items based on anonymous behavior sequences. Most existing SBR studies model the user preferenc…
Target Guided Emotion Aware Chat Machine
Wei Wei, Jiayi Liu, Xianling Mao +5
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge i…