DoRA: Weight-Decomposed Low-Rank Adaptation

from Embodied AI 101 Hosted by Shaoqing Tan

An upgrade over LoRA for parameter-efficient fine-tuning, enabling better performance in LLMs by decomposing weights into magnitude and direction components.

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DoRA: Weight-Decomposed Low-Rank Adaptation

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How long is this episode of Embodied AI 101?

This episode is 39 minutes long.

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This episode was published on April 6, 2026.

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