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Large language models (LMs) offer broad generalization capabilities but require vast amounts of data and computational resources for domain-specific tasks; small models (SMs), in contrast, are more efficient and tailored to specific domains yet lack general-purpose coverage.
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“Machine Unlearning Of Pre-Trained Large Language Models”
Jin Yao et al · 2024
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Yixiang Yao, Fei Wang, Srivatsan Ravi and Muhao Chen · 2024
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“Openfedllm: Training Large Language Models On Decentralized Private Data Via Federated Learning”
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Da Yu, Peter Kairouz, Sewoong Oh and Zheng Xu · 2024
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“Orchestration Of Emulator Assisted 6G Mobile Edge Tuning For AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach”
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“The Good And The Bad: Exploring Privacy Issues In Retrieval-Augmented Generation (RAG)”
Shenglai Zeng et al · 2024
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“Federated Adaptation For Foundation Model-Based Recommendations”
Chun-xu Zhang et al · 2024
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“FedGMKD: An Efficient Prototype Federated Learning Framework Through Knowledge Distillation And Discrepancy-Aware Aggregation”
Jian-qiao Zhang, Cai-feng Shan and Jungong Han · 2024
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“An Upload-Efficient Scheme For Transferring Knowledge From A Server-Side Pre-Trained Generator To Clients In Heterogeneous Federated Learning”
Jianqing Zhang, Yang Liu, Yang Hua and Jian Cao · 2024
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“FedTGP: Trainable Global Prototypes With Adaptive-Margin-Enhanced Contrastive Learning For Data And Model Heterogeneity In Federated Learning”
Jianqing Zhang, Yang Liu, Yang Hua and Jian Cao · 2024
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“One-Shot Federated Learning Via Synthetic Distiller-Distillate Communication”
Junyuan Zhang, Songhua Liu and Xinchao Wang · 2024
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Kaiyan Zhang et al · 2024
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“Cogenesis: A Framework Collaborating Large And Small Language Models For Secure Context-Aware Instruction Following”
Kaiyan Zhang et al · 2024
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“LatticeGen: Hiding Generated Text In A Lattice For Privacy-Aware Large Language Model Generation On Cloud”
Mengke Zhang et al · 2024
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“Privacyasst: Safeguarding User Privacy In Tool-Using Large Language Model Agents”
Xinyu Zhang et al · 2024
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“Chain Of Agents: Large Language Models Collaborating On Long-Context Tasks”
Yu-sen Zhang et al · 2024
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“Large language model watermark stealing with mixed integer programming”
Zhaoxi Zhang et al · 2024
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“Universal Vulnerabilities In Large Language Models: Backdoor Attacks For In-Context Learning”
Shuai Zhao et al · 2024
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“Generate Synthetic Text Approximating The Private Distribution With Differential Privacy”
Wenhao Zhao, Shaoyang Song and Chunlai Zhou · 2024
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“Seeking Neural Nuggets: Knowledge Transfer In Large Language Models From A Parametric Perspective”
Ming Zhong et al · 2024
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“Ipremover: A generative model inversion attack against deep neural network fingerprinting and watermarking”
Wei Zong et al · 2024
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“Fusegen: PLM Fusion For Data-Generation Based Zero-Shot Learning”
Tianyuan Zou et al · 2024
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“Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation”
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“Scaling Trends for Data Poisoning in LLMs”
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Dnyanesh Khedekar, Tanmaya Mahapatra and Amitesh Rajput · 2025
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Senyao Li et al · 2025
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Yige Li et al · 2025
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Saeid Sheikhi, Panos Kostakos and Lauri Loven · 2025
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Haonan Shi, Tu Ouyang and An Wang · 2025
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Jonathan Sneh et al · 2025
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Fali Wang et al · 2025
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