Papers with full-precision fine-tuning

1 papers
Quaff: Quantized Parameter-Efficient Fine-Tuning under Outlier Spatial Stability Hypothesis (2025.acl-long)

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Challenge: Existing methods for quantized fine-tuning fail to address activation outliers . existing methods incur high computational/memory costs or fail to adequately address outlier activation .
Approach: They propose a Quantized parameter-efficient fine-tuning framework that suppresses outliers exclusively in invariant channels using lightweight operations.
Outcome: The proposed framework reduces outliers in invariant channels while reducing quantization errors.

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