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cs.LG2026
Exploring and Exploiting Stability in Latent Flow Matching
Rania Briq, Michael Kamp, Ohad Fried +2
In this work, we show that Latent Flow-Matching (LFM) models are robust to different types of perturbations, including data reduction and model capacity shrinkage. We characterize…
cs.LG2026
Beyond Parameter Aggregation: Semantic Consensus for Federated Fine-Tuning of LLMs
Amr Abourayya, Jens Kleesiek, Michael Kamp
Federated fine-tuning of large language models is commonly formulated as a parameter aggregation problem. However, even parameter-efficient methods require transmitting large colle…