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20232026
most citedA Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment

9 citations · 12 across the 6 of their papers we have counts for

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2 papers · 1 filter

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…

cs.LG2023★ 2 cited

Medical Foundation Models are Susceptible to Targeted Misinformation Attacks

Tianyu Han, Sven Nebelung, Firas Khader +9

Large language models (LLMs) have broad medical knowledge and can reason about medical information across many domains, holding promising potential for diverse medical applications…