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Harvard University
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ReRound outperforms standard quantization techniques by resolving midpoint ambiguity, achieving superior accuracy in low-bit weight quantization for small LLMs.
Achieve state-of-the-art personalized gaze estimation by intelligently reweighting pre-trained features, rather than learning new ones from scratch.
