Applications -- Multi-intent Description of Keyword Expansion for Code Search -- Few-Shot NER in Marine Ecology using Deep Learning -- Knowledge Prompting with Contrastive Learning for Unsupervised Commonsense Question Answering -- PTCP: Alleviate Layer Collapse in Pruning at Initialization via Parameter Threshold Compensation and Preservation -- Hierarchical Attribute-Based Encryption Scheme Supporting Computing Outsourcing and Time-Limited Access in Edge Computing -- An Ontology for Industrial Intelligent Model Library and Its Distributed Computing Application -- Efficient Prompt Tuning for Vision and Language Models -- Spatiotemporal PM2.5 Pollution Prediction Using Cloud-Edge Intelligence -- From Incompleteness to Unity: A Framework for Multi-view Clustering with Missing Values -- PLKA-MVSNet: Parallel Multi-View Stereo with Large Kernel Convolution Attention -- Enhancement of Masked Expression Recognition Inference Via Fusion Segmentation and Classifier -- Semantic Line Detection Using Deep-Hough Network with Attention Mechanism and Strip Convolution -- Adaptive Multi-hop Neighbor Selection for Few-shot Knowledge Graph Completion -- Applications of Quantum Embedding in Computer Vision -- Traffic Accident Forecasting Based on a GrDBN-GPR Model with Integrated Road Features -- Phishing Scam Detection for Ethereum Based on Community Enhanced Graph Convolutional Networks -- DTP: An Open-domain Text Relation Extraction Method -- Exploring the Capability of ChatGPT for Cross-Linguistic Agricultural Document Classification: Investigation and Evaluation.-Multi-Task Feature Self-Distillation for Semi-Supervised Machine Translation -- ADGCN: A Weakly Supervised Framework for Anomaly Detection in Social Networks -- Light Field Image Super-Resolution via Global-View Information Adaptation-Guided Deformable Convolution Network -- Contrastive Learning Augmented Graph Auto-Encoder forGraph Embedding -- Enhancing Spatial Consistency and Class-level Diversity for Segmenting Fine-grained Objects -- Diachronic Named Entity Disambiguation for Ancient Chinese Historical Records -- Construction and Prediction of a Dynamic Multi-Relationship Bipartite Network -- Category-wise Fine-Tuning for Image Multi-label Classification with Partial Labels -- DTSRN: Dynamic Temporal Spatial Relation Network for Stock Ranking Recommendation -- Semantic Segmentation of Multispectral Remote Sensing Images with Class Imbalance Using Contrastive Learning -- ESTNet: Efficient Spatio-Temporal Network for Industrial Smoke Detection -- Algorithm for Generating Tire Defect Images Based on RS-GAN -- Novel-Registrable Weights and Region-Level Contrastive Learning for Incremental Few-Shot Object Detection -- Hybrid U-Net: Instrument Semantic Segmentation in RMIS -- Continual Domain Adaption for Neural Machine Translation -- Neural-Symbolic Reasoning with External Knowledge for Machine Reading Comprehension -- Partial Multi-label Learning via Constraint Clustering -- Abstractive Multi-document Summarization with Cross-Documents Discourse Relations -- MelMAE-VC: Extending Masked Autoencoders to Voice Conversion -- Aspect-level sentiment analysis using dual probability graph convolutional networks (DP-GCN) integrating multi-scale information -- Privacy-preserving Image Classification and Retrieval Scheme over Encrypted Images -- An End-To-End Structure with novel position mechanism and improved EMD for Stock Forecasting -- Multiscale Network with Equivalent Large Kernel Attention for Crowd Counting -- M$^3$FGM:A Node Masking and Multi-granularity Message passing-based Federated Graph Model for Spatial-Temporal Data Prediction -- LenANet: A Length-controllable Attention Network for Source Code Summarization -- Self-Supervised Multimodal Representation Learning for Product Identification and Retrieval.

The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.