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PRICAI 2023: Trends in Artificial Intelligence

Overview of attention for book
Cover of 'PRICAI 2023: Trends in Artificial Intelligence'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Spatial Interpolation Method Based on BP Neural Network with Bellman Equation
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    Chapter 2 Attention Auxiliary Supervision for Continuous Sign Language Recognition
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    Chapter 3 AutoShape: Automatic Design of Click-Through Rate Prediction Models Using Shapley Value
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    Chapter 4 Byzantine-Robust Federated Learning via Server-Side Mixtue of Experts
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    Chapter 5 CDAN: Cost Dependent Deep Abstention Network
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    Chapter 6 Learning and Regression on the Grassmannian
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    Chapter 7 Partial Multi-label Learning with a Few Accurately Labeled Data
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    Chapter 8 Shareable and Inheritable Incremental Compilation in iOOBN
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    Chapter 9 A Dynamic Pricing Strategy in Divided Regions for Ride-Hailing
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    Chapter 10 CANAMRF: An Attention-Based Model for Multimodal Depression Detection
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    Chapter 11 CASSOR: Class-Aware Sample Selection for Ordinal Regression with Noisy Labels
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    Chapter 12 Incomplete Multi-view Weak-Label Learning with Noisy Features and Imbalanced Labels
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    Chapter 13 A Joint Framework with Audio Generation for Rare Gunshot Event Detection
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    Chapter 14 Ancient Chinese Machine Reading Comprehension Exception Question Dataset with a Non-trivial Model
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    Chapter 15 Chinese Macro Discourse Parsing on Generative Fusion and Distant Supervision
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    Chapter 16 GHGA-Net: Global Heterogeneous Graph Attention Network for Chinese Short Text Classification
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    Chapter 17 KSRE-CNER: A Knowledge and Semantic Relation Enhancement Framework for Chinese NER
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    Chapter 18 Low-Frequency Aware Unsupervised Detection of Dark Jargon Phrases on Social Platforms
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    Chapter 19 Multilayer Vision and Language Augmented Transformer for Image Captioning
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    Chapter 20 Neural Machine Translation with an Awareness of Semantic Similarity
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    Chapter 21 Optimizing Answer Representation Using Metric Learning for Efficient Short Answer Scoring
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    Chapter 22 Prompting Generative Language Model with Guiding Augmentation for Aspect Sentiment Triplet Extraction
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    Chapter 23 Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrieval
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    Chapter 24 QURG: Question Rewriting Guided Context-Dependent Text-to-SQL Semantic Parsing
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    Chapter 25 Sarcasm Relation to Time: Sarcasm Detection with Temporal Features and Deep Learning
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    Chapter 26 Self-agreement: A Framework for Fine-Tuning Language Models to Find Agreement Among Diverse Opinions
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    Chapter 27 Self-SLP: Community Detection Algorithm in Dynamic Networks Based on Self-paced and Spreading Label Propagation
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    Chapter 28 Word Segmentation of Hiragana Sentences Using Hiragana BERT
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    Chapter 29 An Empirical Study on Context Length for Open-Domain Dialog Generation
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    Chapter 30 COVER: A Heuristic Greedy Adversarial Attack on Prompt-Based Learning in Language Models
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    Chapter 31 Few-Shot Table-to-Text Generation with Structural Bias Attention
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    Chapter 32 Generalized Knowledge Distillation for Topic Models
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    Chapter 33 Improving Speaker Recognition by Time-Frequency Domain Feature Enhanced Method
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    Chapter 34 Leveraging Dual Encoder Models for Complex Question Answering over Knowledge Bases
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    Chapter 35 Unsupervised Contrastive Learning of Sentence Embeddings Through Optimized Sample Construction and Knowledge Distillation
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    Chapter 36 Automatically Choosing Selection Operator Based on Semantic Information in Evolutionary Feature Construction
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    Chapter 38 Investigating the Existence of Holey Latin Squares via Satisfiability Testing
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    Chapter 39 Leiden Fitness-Based Genetic Algorithm with Niching for Community Detection in Large Social Networks
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    Chapter 40 Non-revisiting Stochastic Search for Automatic Graph Learning
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    Chapter 41 Detecting AI Planning Modelling Mistakes – Potential Errors and Benchmark Domains
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    Chapter 42 Decision Tree Clustering for Time Series Data: An Approach for Enhanced Interpretability and Efficiency
  43. Altmetric Badge
    Chapter 43 The Ethical Evaluation Method of Algorithmic Behavior Based on Computational Experiments
  44. Altmetric Badge
    Chapter 44 Metrics for Evaluating Actionability in Explainable AI
Attention for Chapter 10: CANAMRF: An Attention-Based Model for Multimodal Depression Detection
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Chapter title
CANAMRF: An Attention-Based Model for Multimodal Depression Detection
Chapter number 10
Book title
PRICAI 2023: Trends in Artificial Intelligence
Published in
arXiv, January 2024
DOI 10.1007/978-981-99-7022-3_10
Book ISBNs
978-9-81-997021-6, 978-9-81-997022-3
Authors

Wei, Yuntao, Zhang, Yuzhe, Zhang, Shuyang, Zhang, Hone, Yuntao Wei, Yuzhe Zhang, Shuyang Zhang, Hong Zhang

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 50%
Student > Doctoral Student 1 50%
Readers by discipline Count As %
Computer Science 2 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 January 2024.
All research outputs
#20,448,996
of 25,130,202 outputs
Outputs from arXiv
#575,154
of 1,028,056 outputs
Outputs of similar age
#125,223
of 183,271 outputs
Outputs of similar age from arXiv
#5,706
of 18,625 outputs
Altmetric has tracked 25,130,202 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,028,056 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 183,271 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18,625 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.