Papers by Rishab Balasubramanian

1 papers
Efficient Model Development through Fine-tuning Transfer (2025.emnlp-main)

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Challenge: Modern large language models face a major bottleneck: each new version of a pre-trained model requires expensive and repetitive alignment.
Approach: They propose a method that transfers fine-tuning updates across model versions . they extract the diff vector, which is the difference in parameters induced by fine-uning, from a source model and apply it to the base of a different target model.
Outcome: The proposed method reduces training costs while maintaining model performance.

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