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eess.SP2026
Compressed LLM Reprogramming for Vision-Aided Beam Prediction in Vehicular Networks
Kai Dong, Lei Wang, Changyi Li +2
Large Language Model (LLM) reprogramming-based beam prediction demonstrates strong data efficiency by adapting pretrained language models for vehicle-to-infrastructure (V2I) beam p…
cs.LG2026
Partial Model Sharing Improves Byzantine Resilience in Federated Conformal Prediction
Ehsan Lari, Reza Arablouei, Stefan Werner
We propose a Byzantine-resilient federated conformal prediction (FCP) method that leverages partial model sharing, where only a subset of model parameters is exchanged each round.…
cs.LG2026
Communication-Efficient Byzantine-Robust Federated Conformal Prediction via Partial Sharing
Ehsan Lari, Reza Arablouei, Stefan Werner
We propose PRISM-FCP (Partial shaRing and robust calIbration with Statistical Margins for Federated Conformal Prediction), a communication-efficient Byzantine-robust federated conf…