195 Result(s)
within
Artificial Intelligence
Zhe** Yu
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Article
Inherit or discard: learning better domain-specific child networks from the general domain for multi-domain NMT
Multi-domain NMT aims to develop a parameter-sharing model for translating general and specific domains, such as biology, legal, etc., which often struggle with the parameter interference problem. Existing app...
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Article
3A-COT: an attend-arrange-abstract chain-of-thought for multi-document summarization
Large language models (LLMs) have shown significant promise in single-document summarization (SDS). However, there has been limited exploration in multi-document summarization (MDS). The primary challenge in M...
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Article
Pronunciation guided copy and correction model for ASR error correction
Error correction has proven to be an effective means for refining mistakes produced by Automatic Speech Recognition (ASR) models, thereby contributing to a notable reduction in the Word Error Rate (WER) at the...
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Article
Retraction Note: Virtual reality of recognition technologies of the improved contour coding image based on level set and neural network models
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Article
DRA: dynamic routing attention for neural machine translation with low-resource languages
In recent years, the utilization of deep models has significantly enhanced the performance of neural machine translation (NMT). Nevertheless, the uneven distribution of data leads to critical challenges. Speci...
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Article
Stock price prediction through GRA-WD-BiLSTM model with air quality and weather factors
Accurately predicting stock prices is crucial for reducing investment-related risks in decision-making. Contemporary challenges to financial behavior, posed by environmental issues such as pollution and climat...
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Article
Low resource neural machine translation model optimization based on semantic confidence weighted alignment
The performance of neural machine translation models based on the Transformer architecture is contingent upon the quality of the data. When the training data contains a high proportion of noise, the performanc...
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Article
Robust zero-shot discrete hashing with noisy labels for cross-modal retrieval
Recently, zero-shot hashing methods have been successfully applied to cross-modal retrieval. However, these methods typically assume that the training data labels are accurate and noise-free, which is unrealis...
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Article
A Cognitively Inspired Multi-granularity Model Incorporating Label Information for Complex Long Text Classification
Because the abstracts contain complex information and the labels of abstracts do not contain information about categories, it is difficult for cognitive models to extract comprehensive features to match the co...
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Article
Multimodal sentiment analysis based on cross-instance graph neural networks
Owing to the diversity of social media information, enhancing the accuracy of sentiment analysis for social media necessitates a comprehensive understanding of text and image information. Observing multimodal ...
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Article
Integrating grid features and geometric coordinates for enhanced image captioning
The objective of image captioning is to provide precise descriptions of depicted objects and their relationships. To perform this task, previous studies have mainly relied on region features or a combination o...
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Chapter and Conference Paper
An Efficient Momentum Framework for Face-Voice Association Learning
Cross-modal face-voice association is an active field that utilizes biometric features for cross-modal information retrieval. The primary approach for addressing this task involves utilizing contrastive learni...
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Chapter and Conference Paper
Generating Type-Related Instances and Metric Learning to Overcoming Language Priors in VQA
Visual Question Answering (VQA) is a multimodal task that integrates computer vision and natural language processing. It poses a challenge in the field due to language prior, which is influenced by the dataset...
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Chapter and Conference Paper
An Anomaly Detection Framework for Propagation Networks Leveraging Deep Learning
In the Internet era, communication networks are endless, and all kinds of communication anomalies are also dazzling, so it becomes especially important to detect anomalies in social network communication. Grap...
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Chapter and Conference Paper
Chinese-Vietnamese Cross-Lingual Event Causality Identification Based on Syntactic Graph Convolution
The Chinese-Vietnamese cross-lingual event causality identification aims to identify the cause and effect events from the news text describing the event information and present them in a structured form. The e...
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Chapter and Conference Paper
Cross-Lingual Speaker Transfer for Cambodian Based on Feature Disentangler and Time-Frequency Attention Adaptive Normalization
Given the scarcity of a multi-speaker corpus in Cambodian, conventional methods have shown poor performance in Cambodian speaker tranfer. On the other hand, simply using Chinese-English rich resources to expan...
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Article
A personalized paper recommendation method based on knowledge graph and transformer encoder with a self-attention mechanism
Paper recommendation with personalized methods helps researchers to track the latest academic trends and master cutting-edge academic trends efficiently. Meanwhile, the methods of previous paper recommendation...
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Article
Decoupled spatio-temporal grou** transformer for skeleton-based action recognition
Capturing correlations between joints is crucial in skeleton-based action recognition tasks. Transformer has demonstrated its capability in capturing such correlations. However, conventional Transformer-based ...
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Article
Optimizing traffic efficiency via a reinforcement learning approach based on time allocation
With the increasing scale of urbanization, traffic congestion has caused a severe negative impact on the efficiency of social development. To this end, a series of intelligent traffic light control methods bas...
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Article
Robust Dual-Graph Regularized Deep Matrix Factorization for Multi-view Clustering
The matrix factorization approaches have been widely applied for multi-view clustering since they can effectively explore complementary information contained in the multi-view data. However, some prior knowled...
