Papers by Giuseppe Curci

1 papers
Practical Guidelines for Model Merging in LLMs Pre-Training (2026.acl-industry)

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Challenge: Existing studies on model merging have focused on stable learning rate regimes, but its effectiveness during LLM pre-training remains underexplored.
Approach: They systematically investigate model merging across training phases, focusing on the transition from stable to decaying learning rates.
Outcome: The proposed methods improve performance during stable learning rate regimes but diminish under decay, a phe-nomenon that is linked to reduced checkpoint diversity and lower parameter-space variability.

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