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[논문 리뷰] Semantics-Native Communication via Contextual Reasoning

논문 링크: Semantics-Native Communication via Contextual ReasoningRecently, machine learning (ML) has shown its effectiveness in improving communication efficiency by reinstating the semantics of bits. To understand its underlying principles, we propose a novel stochastic model of semantic communication, dubbed semanticsieeexplore.ieee.org 출처: H. Seo, J. Park, M. Bennis and M. Debbah, "Semantics-Na..

Wireless Communications 2026.01.09

[논문 리뷰] Federated Learning: Challenges, Methods, and Future Directions

논문 링크: Federated Learning: Challenges, Methods, and Future DirectionsFederated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized. Training in heterogeneous and potentially massive networks introduces novel challenges thaieeexplore.ieee.org 출처: T. Li, A. K. Sahu, A. Talwalkar and V. Smith, "F..

Artificial Intelligence 2025.12.23
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pilotcontamination, Ai, semantic learning, Large Language Model, contextual reasoning, Semantic communications, beyond 6G, energy efficiency, 6g, semantic communication, Federated Learning, massive MIMO systems, time-division duplexing (TDD), AI-native, Intelligent wireless networks, Joint source-channel coding, spectral efficiency, ML, orthogonal frequency division multiplexing (OFDM), Channel estimation,

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