Neural Information Processing 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2–6, 2024, Proceedings, Part XII

The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024.
The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.

Fine-tuning Fine-tuned Models: Towards a Practical Methodology for Sentiment Analysis with Small In-domain Supervised Dataset.- End-to-end Knowledge Graph Construction System Powered by Large
Language Models.- EPRVR: Efficient Partially Relevant Video Retrieval with Disentangled Video Representation Learning.- Graph-Based Data Augmentation and Label Noise Identification for
Entity Resolution.- Patient Mortality prediction Using Clinical Notes.- ScaleDoc: A Two-Stage Approach for Scale-Aware Document Dewarping.- CCUH:CLIP-Based Clustering Method for Unsupervised Hashing Multi-Modal Retrieval.- A Privacy-Preserving Image Classification Framework with Transformer.- Reversible Data Hiding in Dual Encrypted Images with Dual Data Embedding.- A Dual-Layer Reversible Data Hiding Scheme Based on Optimal Neighbor Mean Interpolation (ONMI) and Histogram Shifting.- Threat Intelligence Entity Recognition Based On Large Language Model With Contrastive Learning.- GTSD: Generative Text Steganography Based on Diffusion Model.- Enhanced Autoencoder Model for Robust Anomaly Detection in Financial Fraud with Imbalanced Data.- Membership Inference Attacks in Text Classification Tasks.- PURVEY-CE: A Complex texture adaptive image steganography based on channel attention.- Air-Sniffing Analytics Enhancing Wi-Fi Device Identification with Robust and Accurate Techniques.- Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devices.- Control ControlNet: Multidimensional Backdoor Attack based on ControlNet.- CPANet: Convolutional Parameter Adapter Network for Image
Copy-Move Forgery Detection and Localization.- AO-UAP: An Adaptive Universal Adversarial Perturbation Generation for Speech Recognition Models.- A Hilbert-Curve based Encoding scheme for Privacy-preserving Nearest-Neighbor Classification.- ZKP-HGNN: A Study on Improving Zero- Knowledge Proof (ZKP) Based on Heterogeneous Graph Neural Networks for Anonymous Digital Identity Sharing in Blockchain.- Adversarial Knowledge Extraction via Steering Diffusion Models.- Solving the Thinnest Path Problem with Hypergraph Learning.- AISSGR: Attack Investigation Based on Self-Supervised Graph Representation Learning.- Two-stage optimized adversarial patch for attacking infrared vehicle detectors in the physical world.- Deep Learning-Based Detection of Code Execution Vulnerabilities in Binary Programs.- Towards Real-Time Audio Deepfake Detection in Resource-Limited
Environments.- Detecting Audio Deepfakes through Emotional Fingerprinting.- Constructing Multi-Detector Decision Forest for Fake Speech Detection.- KDAE: Kernel Density Auto-Encoder for Semi-Supervised Anomaly Detection with Limited Labeled Data.