AFedLF: Adaptive Layer Freezing of Foundation Models in Heterogeneous Federated Learning

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Optimizing Prompts With MLLM for Multimodal Product Style Recognition in Industry 5.0

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Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models

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Advanced Product Personalization in Blockchain-Enabled Metaverse: A Diffusion Model for Automatic Style Generation

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Collaborative Neural Architecture Search for Personalized Federated Learning

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Data Quality-Aware Mixed-Precision Quantization via Hybrid Reinforcement Learning

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Feature Correlation-Guided Knowledge Transfer for Federated Self-Supervised Learning

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Large Language Model Offloading using Active Inference in 6G Symbiotic IoT

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Metaverse Oriented User Preference Recom-mendation Systems Based on DSD-Transformer

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Model Decomposition and Reassembly for Purified Knowledge Transfer in Personalized Federated Learning

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MycoStore:A Layer-Sharing Neural Network Model Repository for 6G Edge Intelligence

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BoxSeg: Quality-Aware and Peer-Assisted Learning for Box-supervised Instance Segmentation

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Causm: Causally Motivated Sycophancy Mitigation For Large Language Models

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DiEP: Adaptive Mixture-of-Experts Compression through Differentiable Expert Pruning

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Exploring prosocial irrationality for LLM agents: a social cognition view

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Uni-IL: Unified Incremental Learning of Vision-Language Models via Mixture of Attribute-Guided Experts

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VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting

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A Sustainable Supply Chain Design for Personalized Customization in Industry 5.0 Era

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Human Cognition Modeling for the Metaverse-Oriented Design System

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SafeDRL: Dynamic Microservice Provisioning With Reliability and Latency Guarantees in Edge Environments

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Social Group Oriented Recommendation Systems in Wireless Edge-Empowered Metaverse

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Towards performance-maximizing neural network pruning via global channel attention

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Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models

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Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization

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Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

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DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning

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Dual Expert Distillation Network for Generalized Zero-Shot Learning

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LEARNING PERSONALIZED CAUSALLY INVARIANT REPRESENTATIONS FOR HETEROGENEOUS FEDERATED CLIENTS

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On the Robustness of Neural-Enhanced Video Streaming against Adversarial Attacks

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OTAS: An Elastic Transformer Serving System via Token Adaptation

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ParsNets: A Parsimonious Composition of Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning

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SFP: Spurious Feature-Targeted Pruning for Out-of-Distribution Generalization

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Towards Safe Concept Transfer of Multi-Modal Diffusion via Causal Representation Editing

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From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization

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RuleDRL: Reliability-Aware SFC Provisioning With Bounded Approximations in Dynamic Environments

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Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning

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Opponent Modeling Based Dynamic Resource Trading for UAV-Assisted Edge Computing

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Prophet: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering

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SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models

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Towards Fairer and More Efficient Federated Learning via Multidimensional Personalized Edge Models

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Towards Unbiased Training in Federated Open-world Semi-supervised Learning

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A Survey of Incentive Mechanism Design for Federated Learning

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Adaptive Federated Learning on Non-IID Data With Resource Constraint

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Adaptive Vertical Federated Learning on Unbalanced Features

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Edge Learning: The Enabling Technology for Distributed Big Data Analytics in the Edge

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Federated Unlearning: Guarantee the Right of Clients to Forget

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Hierarchical Channel-spatial Encoding for Communication-efficient Collaborative Learning

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Layer-wised Model Aggregation for Personalized Federated Learning

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Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression

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Parameterized Knowledge Transfer for Personalized Federated Learning

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Dual-view Attention Networks for Single Image Super-Resolution

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Multi-path routing oriented flow statistics collection in software defined networks

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