271 citations · 286 across the 11 of their papers we have counts for
13 papers
Type-Balanced Contextual Learning for Incremental Named Entity Recognition
Duzhen Zhang, Yahan Yu, Xiuyi Chen +2
Incremental Named Entity Recognition (INER) stands as a pivotal task in information extraction, emphasizing the successive identification of new entity types within unstructured te…
Continual Named Entity Recognition without Catastrophic Forgetting
Duzhen Zhang, Wei Cong, Jiahua Dong +4
Continual Named Entity Recognition (CNER) is a burgeoning area, which involves updating an existing model by incorporating new entity types sequentially. Nevertheless, continual le…
Task Relation Distillation and Prototypical Pseudo Label for Incremental Named Entity Recognition
Duzhen Zhang, Hongliu Li, Wei Cong +3
Incremental Named Entity Recognition (INER) involves the sequential learning of new entity types without accessing the training data of previously learned types. However, INER face…
Matching-based Term Semantics Pre-training for Spoken Patient Query Understanding
Zefa Hu, Xiuyi Chen, Haoran Wu +5
Medical Slot Filling (MSF) task aims to convert medical queries into structured information, playing an essential role in diagnosis dialogue systems. However, the lack of sufficien…
Crucial Semantic Classifier-based Adversarial Learning for Unsupervised Domain Adaptation
Yumin Zhang, Yajun Gao, Hongliu Li +3
Unsupervised Domain Adaptation (UDA), which aims to explore the transferrable features from a well-labeled source domain to a related unlabeled target domain, has been widely progr…
Consecutive Knowledge Meta-Adaptation Learning for Unsupervised Medical Diagnosis
Yumin Zhang, Yawen Hou, Xiuyi Chen +2
Deep learning-based Computer-Aided Diagnosis (CAD) has attracted appealing attention in academic researches and clinical applications. Nevertheless, the Convolutional Neural Networ…
HiVLP: Hierarchical Vision-Language Pre-Training for Fast Image-Text Retrieval
Feilong Chen, Xiuyi Chen, Jiaxin Shi +3
In the past few years, the emergence of vision-language pre-training (VLP) has brought cross-modal retrieval to a new era. However, due to the latency and computation demand, it is…
Improving Cross-Modal Understanding in Visual Dialog via Contrastive Learning
Feilong Chen, Xiuyi Chen, Shuang Xu +1
Visual Dialog is a challenging vision-language task since the visual dialog agent needs to answer a series of questions after reasoning over both the image content and dialog histo…
TSAM: A Two-Stream Attention Model for Causal Emotion Entailment
Duzhen Zhang, Zhen Yang, Fandong Meng +2
Causal Emotion Entailment (CEE) aims to discover the potential causes behind an emotion in a conversational utterance. Previous works formalize CEE as independent utterance pair cl…
VLP: A Survey on Vision-Language Pre-training
Feilong Chen, Duzhen Zhang, Minglun Han +4
In the past few years, the emergence of pre-training models has brought uni-modal fields such as computer vision (CV) and natural language processing (NLP) to a new era. Substantia…
Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation
Feilong Chen, Fandong Meng, Xiuyi Chen +2
Visual dialogue is a challenging task since it needs to answer a series of coherent questions on the basis of understanding the visual environment. Previous studies focus on the im…
GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
Feilong Chen, Xiuyi Chen, Fandong Meng +2
Visual dialog, which aims to hold a meaningful conversation with humans about a given image, is a challenging task that requires models to reason the complex dependencies among vis…
Learning to Ground Visual Objects for Visual Dialog
Feilong Chen, Xiuyi Chen, Can Xu +1
Visual dialog is challenging since it needs to answer a series of coherent questions based on understanding the visual environment. How to ground related visual objects is one of t…