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- short-paperJuly 2024
ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2024, Pages 2781–2785https://doi.org/10.1145/3626772.3657680Crafting the ideal, job-specific resume is a challenging task for many job applicants, especially for early-career applicants. While it is highly recommended that applicants tailor their resume to the specific role they are applying for, manually ...
- research-articleJuly 2024JUST ACCEPTED
Self-Supervised EEG Representation Learning for Robust Emotion Recognition
Emotion recognition based on electroencephalography (EEG) is becoming a growing concern of researchers due to its various applications and portable devices. Existing methods are mainly dedicated to EEG feature representation and have made impressive ...
- research-articleJuly 2024
Fusion learning of preference and bias from ratings and reviews for item recommendation
Data & Knowledge Engineering (DAKE), Volume 150, Issue CMar 2024https://doi.org/10.1016/j.datak.2024.102283AbstractRecommendation methods improve rating prediction performance by learning selection bias phenomenon-users tend to rate items they like. These methods model selection bias by calculating the propensities of ratings, but inaccurate propensity could ...
Highlights- Using reviews to model interaction features and selection bias.
- Modeling word distribution bias and review quoting to extract review features.
- A preference- and bias-oriented fusion learning (PBFL) model is proposed.
- The method ...
- research-articleJuly 2024
Effects of 1,4-dihydropyridine derivatives on cell injury and mTOR of HepG2 and 3D-QSAR study
Computational Biology and Chemistry (COBC), Volume 109, Issue CApr 2024https://doi.org/10.1016/j.compbiolchem.2023.108010Abstract1,4-dihydropyridine derivatives (1,4-DHPs) are a class of drugs used to treat cardiovascular diseases, but these drugs can cause liver injury. To reveal the toxicity characteristics of these compounds, we used a series of assays, including cell ...
Graphical AbstractDisplay Omitted
Highlights- The model of 1,4-DHPs toxicity prediction is established by cytotoxicity test.
- The method is used to predict the toxicity of 1,4-DHPs.
- The model is built by the CoMSIA with good stability and predictive ability.
- research-articleJuly 2024
Frequency-aware network for low-light image enhancement
Computers and Graphics (CGRS), Volume 118, Issue CFeb 2024, Pages 210–219https://doi.org/10.1016/j.cag.2023.12.014AbstractLow-light images often suffer from severe visual degradation, affecting both human perception and high-level computer vision tasks. Most existing methods process images in the spatial domain, making it challenging to simultaneously improve ...
Graphical abstractDisplay Omitted
Highlights- We reveal that the luminance is closely related to low-frequency components.
- We design a frequency-aware network to utilize frequency domain features.
- A multi-scale framework and selective fusion is proposed for feature learning.
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- research-articleJuly 2024
(Vision Paper) A Vision for Spatio-Causal Situation Awareness, Forecasting, and Planning
- Fahim Tasneema Azad,
- K. Selçuk Candan,
- Ahmet Kapkiç,
- Mao-Lin Li,
- Huan Liu,
- Pratanu Mandal,
- Paras Sheth,
- Bilgehan Arslan,
- Gerardo Chowell-Puente,
- John Sabo,
- Rebecca Muenich,
- Javier Redondo Anton,
- Maria Luisa Sapino
ACM Transactions on Spatial Algorithms and Systems (TSAS), Volume 10, Issue 2Article No.: 14, Pages 1–42https://doi.org/10.1145/3672556Successfully tackling many urgent challenges in socio-economically critical domains, such as public health and sustainability, requires a deeper understanding of causal relationships and interactions among a diverse spectrum of spatio-temporally ...
- research-articleJune 2024
Upgrading swin-B transformer-based model for accurately identifying ripe strawberries by coupling task-aligned one-stage object detection mechanism
Computers and Electronics in Agriculture (COEA), Volume 218, Issue CMar 2024https://doi.org/10.1016/j.compag.2024.108674Highlights- Presenting anchor point alignment technique for strawberry ripeness detection.
- Incorporating the Swin-B attention mechanism into the strawberry feature extraction model.
- Employing the CARAFE module to upsample the detailed ...
With the wave of agricultural modernization, deep learning technology has brought revolutionary changes to the vision system of strawberry picking robots. Yet, the morphological diversity of strawberries, small and dense targets, and high overlap ...
- research-articleJune 2024
Lightweight algorithm for strip steel surface defect detection based on feature enhancement
AIPR '23: Proceedings of the 2023 6th International Conference on Artificial Intelligence and Pattern RecognitionSeptember 2023, Pages 246–252https://doi.org/10.1145/3641584.3641621Abstract: The small size of strip surface defects, dense defect distribution, and high background noise leads to the problems of poor detection accuracy and real-time detectability of general-purpose target detection algorithms in detecting strip surface ...
- research-articleJune 2024
Intelligent Retrieval System for Power Policy Documents Based on Semantic Analysis
AISNS '23: Proceedings of the 2023 International Conference on Artificial Intelligence, Systems and Network SecurityDecember 2023, Pages 227–232https://doi.org/10.1145/3661638.3661684In recent years, the frequent release and large volume of power policy documents have led to common issues in the application process, including time-consuming comprehensive document review, inconvenient document retrieval, and difficulties in ...
- research-articleMay 2024
Application of information technology in education--- CiteSpace-based visualisation and analysis
ICIEAI '23: Proceedings of the 2023 International Conference on Information Education and Artificial IntelligenceDecember 2023, Pages 529–534https://doi.org/10.1145/3660043.3660138With the development of information technology such as the Internet, big data, and artificial intelligence, the application of information technology in education has received attention from researchers. In this paper, we used CiteSpace software to do a ...
- ArticleMay 2024
Adversarial Text Purification: A Large Language Model Approach for Defense
Advances in Knowledge Discovery and Data MiningMay 2024, Pages 65–77https://doi.org/10.1007/978-981-97-2262-4_6AbstractAdversarial purification is a defense mechanism for safeguarding classifiers against adversarial attacks without knowing the type of attacks or training of the classifier. These techniques characterize and eliminate adversarial perturbations from ...
- research-articleMay 2024
Hyperspectral and Multi-source Heterogeneous Data Fusion Classification Based on Multiscale Multi-source Interaction Attention Network
ICIGP '24: Proceedings of the 2024 7th International Conference on Image and Graphics ProcessingJanuary 2024, Pages 217–223https://doi.org/10.1145/3647649.3647685With the development of remote sensing technology, the performance varies among different sensors, and multi-source data fusion is widely concerned. However, existing methods often fall short in extracting rich features from multi-source data and tend to ...
- research-articleApril 2024
Power Grid Fault Diagnosis Based on Knowledge Graph and Bayesian Inference
ICCSMT '23: Proceedings of the 2023 4th International Conference on Computer Science and Management TechnologyOctober 2023, Pages 657–662https://doi.org/10.1145/3644523.3644643This paper integrates Knowledge Graph, Scale-free Network, and Bayesian Network for fault diagnosis of the power grid. The proposed model combines Knowledge Graph based on typical accident reports with the Scale-free Network model to establish and ...
- articleMarch 2024
Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?
ACM SIGKDD Explorations Newsletter (SIGKDD), Volume 25, Issue 2December 2023, Pages 14–21https://doi.org/10.1145/3655103.3655106Large language models (LLMs) such as ChatGPT are increasingly being used for various use cases, including text content generation at scale. Although detection methods for such AI-generated text exist already, we investigate ChatGPT's performance as a ...
- research-articleMarch 2024
Quantifying the Echo Chamber Effect: An Embedding Distance-based Approach
ASONAM '23: Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningNovember 2023, Pages 38–45https://doi.org/10.1145/3625007.3627731The rise of social media platforms has facilitated the formation of echo chambers, which are online spaces where users predominantly encounter viewpoints that reinforce their existing beliefs while excluding dissenting perspectives. This phenomenon ...
- research-articleMarch 2024
PADVG: A Simple Baseline of Active Protection for Audio-Driven Video Generation
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 20, Issue 6Article No.: 168, Pages 1–19https://doi.org/10.1145/3638556Over the past few years, deep generative models have significantly evolved, enabling the synthesis of realistic content and also bringing security concerns of illegal misuse. Therefore, active protection for generative models has been proposed recently, ...
- research-articleMarch 2024
Causality Guided Disentanglement for Cross-Platform Hate Speech Detection
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data MiningMarch 2024, Pages 626–635https://doi.org/10.1145/3616855.3635771espite their value in promoting open discourse, social media plat- forms are often exploited to spread harmful content. Current deep learning and natural language processing models used for detect- ing this harmful content rely on domain-specific terms ...
- research-articleMarch 2024
FECAM: Frequency enhanced channel attention mechanism for time series forecasting
Advanced Engineering Informatics (ADEI), Volume 58, Issue COct 2023https://doi.org/10.1016/j.aei.2023.102158AbstractTime series forecasting (TSF) is a challenging problem in various real-world scenarios, such as industry, energy, weather, traffic, economics, and earthquake warning. TSF demands the model to have a high prediction accuracy. Despite the promising ...
- research-articleFebruary 2024
Robust Graph Meta-Learning for Weakly Supervised Few-Shot Node Classification
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 4Article No.: 83, Pages 1–18https://doi.org/10.1145/3630260Graph machine learning (Graph ML) models typically require abundant labeled instances to provide sufficient supervision signals, which is commonly infeasible in real-world scenarios since labeled data for newly emerged concepts (e.g., new categorizations ...