most citedDynamic Causal Disentanglement Model for Dialogue Emotion Detection

2 citations · 5 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CR20231 cited

My Brother Helps Me: Node Injection Based Adversarial Attack on Social Bot Detection

Lanjun Wang, Xinran Qiao, Yanwei Xie +3

Social platforms such as Twitter are under siege from a multitude of fraudulent users. In response, social bot detection tasks have been developed to identify such fake users. Due…

cs.CL20232 cited

Dynamic Causal Disentanglement Model for Dialogue Emotion Detection

Yuting Su, Yichen Wei, Weizhi Nie +2

Emotion detection is a critical technology extensively employed in diverse fields. While the incorporation of commonsense knowledge has proven beneficial for existing emotion detec…

cs.AI20231 cited

Reinforcement Learning Based Multi-modal Feature Fusion Network for Novel Class Discovery

Qiang Li, Qiuyang Ma, Weizhi Nie +1

With the development of deep learning techniques, supervised learning has achieved performances surpassing those of humans. Researchers have designed numerous corresponding models…

cs.LG2023

Causal Disentanglement Hidden Markov Model for Fault Diagnosis

Rihao Chang, Yongtao Ma, Weizhi Nie +2

In modern industries, fault diagnosis has been widely applied with the goal of realizing predictive maintenance. The key issue for the fault diagnosis system is to extract represen…

cs.LG2023

Temporal-spatial Correlation Attention Network for Clinical Data Analysis in Intensive Care Unit

Weizhi Nie, Yuhe Yu, Chen Zhang +3

In recent years, medical information technology has made it possible for electronic health record (EHR) to store fairly complete clinical data. This has brought health care into th…

eess.IV2023

Deep Reinforcement Learning Framework for Thoracic Diseases Classification via Prior Knowledge Guidance

Weizhi Nie, Chen Zhang, Dan Song +4

The chest X-ray is often utilized for diagnosing common thoracic diseases. In recent years, many approaches have been proposed to handle the problem of automatic diagnosis based on…