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arXiv Machine Learning By Farhad Rezazadeh, Hatim Chergui, Amir Ashtari Gargari, Mehdi Bennis, Houbing Song, Lingjia Liu, Merouane Debbah

LiQSS: Post-Transformer Linear Quantum-Inspired State-Space Tensor Networks for Real-Time 6G

Read the original on arXiv Machine Learning →

arXiv:2601. 12375v3 Announce Type: replace-cross Abstract: Proactive and agentic control in Sixth-Generation (6G) Open Radio Access Networks (O-RAN) requires control-grade prediction under stringent Near-Real-Time (Near-RT) latency and computational constraints.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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