Showing 1–20 of 26 results
/ Date/ Name
Apr 14, 2021ABEM: An Adaptive Agent-based Evolutionary Approach for Mining Influencers in Online Social NetworksApr 29, 2021Applications of Artificial Intelligence to aid detection of dementia: a narrative review on current capabilities and future directionsJul 6, 2022A Comprehensive Review on Deep Supervision: Theories and ApplicationsApr 7, 2024Balancing Information Perception with Yin-Yang: Agent-Based Information Neutrality Model for Recommendation SystemsOct 31, 2022Hybrid CNN -Interpreter: Interpret local and global contexts for CNN-based ModelsMar 9, 2025Towards Superior Quantization Accuracy: A Layer-sensitive ApproachFeb 23, 2026Depth-Structured Music Recurrence: Budgeted Recurrent Attention for Full-Piece Symbolic Music ModelingMay 15, 2019Specifying and Reasoning about Contextual Preferences in the Goal-oriented Requirements ModellingJul 13, 2021Identifying Influential Users in Unknown Social Networks for Adaptive Incentive Allocation Under Budget RestrictionMar 17, 2022GAC: A Deep Reinforcement Learning Model Toward User Incentivization in Unknown Social NetworksOct 18, 2022Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image GenerationFeb 2, 2023DOR: A Novel Dual-Observation-Based Approach for News Recommendation SystemsJan 18, 2023Rapid-Motion-Track: Markerless Tracking of Fast Human Motion with Deeper LearningMar 1, 2023Soft Prompt Guided Joint Learning for Cross-Domain Sentiment AnalysisJan 12, 2026Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation StrategiesFeb 19, 2024Detecting misinformation through Framing Theory: the Frame Element-based ModelDec 19, 2021Parallel Multi-Scale Networks with Deep Supervision for Hand Keypoint DetectionNov 19, 2022A Light-weight, Effective and Efficient Model for Label Aggregation in CrowdsourcingMay 26, 2023AaKOS: Aspect-adaptive Knowledge-based Opinion SummarizationJul 6, 2023BHEISR: Nudging from Bias to Balance -- Promoting Belief Harmony by Eliminating Ideological Segregation in Knowledge-based Recommendations