Papers with low-rank estimations

1 papers
LoRE-Merging: Exploring Low-Rank Estimation For Large Language Model Merging (2025.findings-emnlp)

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Challenge: a framework for model merging is proposed without additional training . task vectors from fine-tuned models exhibit a limited number of dominant singular values .
Approach: They propose a framework for model merging based on low-rank estimation of task vectors without access to the base model.
Outcome: The proposed framework improves models without additional training without additional inputs.

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