A5040290728- Speech and dialogue systems
- Topic Modeling
- Natural Language Processing Techniques
- Mycotoxins in Agriculture and Food
- EEG and Brain-Computer Interfaces
- Advanced Chemical Sensor Technologies
- Spectroscopy and Chemometric Analyses
Xi'an Jiaotong University
2023-2024
Chinese University of Hong Kong
2023-2024
Xiaomi (China)
2023-2024
Xidian University
2024
Ministry of Education of the People's Republic of China
2018
Jiangsu University
2018
Visual diagnosis of plant disease following a visually evident epidemic results in untimely and excessive application pesticide. Conventional nondestructive testing methods are difficult for early recognition before the onset symptoms. In this study, tomato mosaic wheat leaf rust were taken as examples. Infrared thermal imaging technology was used to continuously detect temperature information two crops during incubation period introduction inoculum. Diseases induced by rubbing inoculation...
Reasoning, a crucial aspect of NLP research, has not been adequately addressed by prevailing models including Large Language Model. Conversation reasoning, as critical component it, remains largely unexplored due to the absence welldesigned cognitive model. In this paper, inspired intuition theory on conversation cognition, we develop model (CCM) that explains how each utterance receives and activates channels information recursively. Besides, algebraically transformed CCM into structural...
Early diagnosis of Alzheimer's disease (AD) is crucial for its prevention, and hippocampal atrophy a significant lesion early diagnosis. The current DL-based AD methods only focus on either classification or hippocampus segmentation independently, neglecting the correlation between two tasks lacking pathological interpretability. To address this issue, we propose Reliable Hippo-guided Learning model Disease (RLAD), which employs multi-task learning as main task supplemented by segmentation....
Our investigation into the Affective Reasoning in Conversation (ARC) task highlights challenge of causal discrimination. Almost all existing models, including large language models (LLMs), excel at capturing semantic correlations within utterance embeddings but fall short determining specific relationships. To overcome this limitation, we propose incorporation \textit{i.i.d.} noise terms conversation process, thereby constructing a structural model (SCM). It explores how distinct...
Reasoning, a crucial aspect of NLP research, has not been adequately addressed by prevailing models including Large Language Model. Conversation reasoning, as critical component it, remains largely unexplored due to the absence well-designed cognitive model. In this paper, inspired intuition theory on conversation cognition, we develop model (CCM) that explains how each utterance receives and activates channels information recursively. Besides, algebraically transformed CCM into structural...