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20222026
most citedA Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment

9 citations · 15 across the 13 of their papers we have counts for

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Showing 2026Show all

2 papers · 1 filter

cs.LG2026

Trade-offs in Ensembling, Merging and Routing Among Parameter-Efficient Experts

Sanae Lotfi, Lucas Caccia, Alessandro Sordoni +2

While large language models (LLMs) fine-tuned with lightweight adapters achieve strong performance across diverse tasks, their performance on individual tasks depends on the fine-t…

cs.LG2026

Learning to Solve Complex Problems via Dataset Decomposition

Wanru Zhao, Lucas Caccia, Zhengyan Shi +3

Curriculum learning is a class of training strategies that organizes the data being exposed to a model by difficulty, gradually from simpler to more complex examples. This research…