Advanced Intelligent Computing Technology and Applications: 21st International Conference, ICIC 2025, Ningbo, China, July 26–29, 2025, Proceedings, Part X(15851 Lecture Notes in Computer Science)

This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The total of 1206 regular papers were carefully reviewed and selected from 4032 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".

Table of Contents:
.- Machine Learning. .- A Bayesian Inference-Enhanced Evolutionary Algorithm for Sleep Scheduling of Software-Defined Radio Sensors. .- A Deep Clustering Method for Single-cell Data Based on Low Rank Representation. .- GNNHacker: Adaptive Subgraph Backdoor Attacking Method with Saliency Analysis and Joint Optimization. .- Knowledge-Constrained Intelligent Learning for Agricultural Yield Prediction in Complex Cropping Systems. .- Formal Theorem Generation via MCTS with LLM-Guided Process Optimization. .- ENGCL: Graph Contrastive Learning via Ego-Preservation and Neighborhood Learning. .- Retrieval and Ranking Model of Scientific Literature Based on MiniLM Formula and AHP. .- MSAF-YOLOv11: Multi-Scale Self-Adaptive Fusion Module for Efficient and Robust Detection in Underground Coal Mining. .- A Federated Active Learning Based on Prototype-Based Hierarchical Clustering. .- FedEPA: Enhancing Personalization and Modality Alignment in Multimodal Federated Learning. .- RG3: Mitigating Memorization of Graph Diffusion Model in One Denoising Step. .- True-to-Life Behavior Relationship Modeling for Multi-behavior Recommendation. .- Multi-Task Learning Based on Dense Feature Pyramid Network and Multi Scale Attention for Class-Imbalanced Hyperspectral Image Class. .- Multi-range Random Walk based Graph Neural Network. .- TinyVision: Distributed Vision-Language Model with Efficiency and Privacy for Edge Deployment. .- A Novel Multi-stage Ensemble Method for Noisy Labels Using Sample Selection and Label Correction. .- Smart Contract Vulnerability Detection with Feature-Enhancement and Self Supervised Training. .- FedSatch: A Dynamic Framework for Enhancing Original Sample Utilisation in Federated Semi-Supervised Learning. .- ARMQwen2: Enhancing C Language Decompilation on ARM Platform Using Large Language Model. .- Gaze-Driven Active Speaker Detection in Meetings. .- A Lyapunov-Based Convex Optimal Control Approach via Input Convex Transformer. .- Unpaired Image Style Translations Using Mamba Adversarial Networks. .- Personalized Incentive Mechanism in Federated Learning via Variational Expectation Maximization. .- Multi-Level Dynamic Gated Interaction Fusion Network for Remote Sensing Visual Question Answering. .- CPTCP: Incorporating Convolutional Neural Network into Text-Vector Based Test Case Prioritization for Compilers. .- GEETI: Graph Embedding-Enhanced Textual Inversion for Chinese Harmful Meme Detection and Identification. .- Abstractive Model for Enhanced Text Summarization through Contrastive Learning to Boost T5 Representations. .- MLPF-Net: Multi-Level Progressive Fusion and Cross-Domain Attention Network for Multi-Modality Image Fusion. .- Contrastive Learning for Robust Time Series Anomaly Detection in Cyber Physical Systems. .- A Trapezoidal Fuzzy Broad Learning System Based on Distance Correlation. .- Accurate Classification for Government Data: A Tree-of-Thoughts-Driven Few-Shot Learning Approach. .- An Efficient Attention-Enhanced Diffusion Model for Surface Defect Detection. .- FedBKT: Federated Learning with Model Heterogeneity via Bidirectional Knowledge Transfer with Mediator Model. .- Partitioned Dual Weighting Strategy for Combining Regression Estimates. .- Memory-Enhanced Cognitive Planning: A Framework for Improving Long Term Planning in LLM. .- A Defense Against Label Flipping Attacks in Federated Learning Using Output Layer Gradients. .- Causal Pathway-Integrated Generative Adversarial Networks for Counterfactually Fair Data Generation. .- Mitigating Heterogeneous Instance-Dependent Label Noise in Federated Learning. .- FPGA-Based Processing-in-Memory with Optimized Multi-BRAM Reduction for Improved Latency-Cost Trade-off. .- DRFormer: Dynamic Replay-Driven Transformer for Domain-Incremental Learning in Brain Tumor Segmentation. .- A Novel Transformer Architecture for Runoff Forecasting. .- FedAF: Federated Learning Framework Based on Attention Mechanisms and Fisher Information Matrix. .- Application of Electronic Tongue Combined with DDPM-CNN-Transformer Hybrid Model for Longjing Tea Origin Detection.