Description
Book Synopsis.- ACL:Adaptive Chunking of Large Language Models for Efficient Inference on Automotive Edge Devices.
.- The Evaluation of Parameter-agnostic Unlearning Mechanisms on Prevailing Large Language Models.
.- Node Centrality Approximation in Complex Networks via Inductive Graph Neural Networks.
.- Carbon Market Price Prediction Method Based on Multi-feature Fusion and Deep Learning.
.- MMtuning: An Advanced Multi-Adapter Framework for Efficient Multimodal Large Language Models Fine-Tuning.
.- Multi-Sensor Fusion Framework for HAR: Integrating Time-Frequency Features and Self-Supervised Learning.
.- Deep Reinforcement Learning-Based Client Selection and Secure Aggregation for Federated Learning.
.- DynamicFedPEFT: Efficient fine-tuning of dynamic federated parameters for large language models.
.- Dynamic, Multi-Scale, and Noise-Aware Modeling for Skeleton Action Prediction.
.- Adaptive Retrieval Enhancement for Open-Domain Question Answering.
.- Privacy-Preserving Exact Closest Vertex Queries on Encrypted Attributed Knowledge Graphs.
.- Text Attributed Graph Node Classification Using Sheaf Neural Networks and Large Language Models.
.- TIEBN: An Eigenvalue-Driven Blockchain Network for Anomaly Detection.
.- Enhanced Knowledge Tracing via Imputing Knowledge States.
.- Resisting Catastrophic Recall: Persistent Unlearning via Knowledge Distillation with Feature Suppression.
.- Enhancing Legal Judgment Prediction in LLMs via Legal Norms Integration.
.- Geo-DETR: Geographical Map Detection Based on Multi-Stage Gradient Feature Fusion.
.- FATFI: A Framework to Generate Adversarial Traffic with Feature Interpretability.
.- Enhancing Multi-Source Localization via Tailored Feature Representation Framework.
.- FedMP: A Multi-Prototype Heterogeneous Federated Learning Framework.
.- CGM: Intrusion Detection Based on a Multi-Head Attention Optimization Model.
.- FusionMIA: Enhancing Membership Inference Attacks with Spy Clients and Shadow Models in Federated Learning.
.- DynaKiteQuery: Top-k Closest-Vertex Queries on Dynamic Attributed Knowledge Graphs.
.- Evaluating LLMs for Multi-label Text Classification.
.- Generating Feedback for School Students Essay with Large Language Models.
.- Dynamic Asymmetric Contrastive Learning with Adaptive Hard Negative Mining for Resume-Job Matching.
.- TRIAD: A Tool-Responsive Instruction-Aligned framework for domain-specific problem solving.
.- Verifiable fine-grained federated unlearning.
.- MCC: Multi-level Feature and Context-aware Attention Mechanism with Consistent Distributions for Recipe Retrieval.
.- Heuristic Ant Colony enabled Federataed UAV Circuit Inspection Planning Algorithm Considering Adaptive Weather.
.- Context-aware Spatiotemporal Graph Attention Network for Next POI Recommendation.
.- From Thinking to Output: Chain-of-Thought and Text Generation Characteristics in Reasoning Language Models.
