Papers by Martino Dazzi
KurTail : Kurtosis-based LLM Quantization (2025.findings-emnlp)
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| Challenge: | Outliers in quantization of large language models make uniform quantization schemes less effective . a new PTQ scheme that leverages Kurtosis-based rotation mitigates outliers . |
| Approach: | They propose a new post-training quantization scheme that leverages Kurtosis-based rotation to mitigate outliers in the activations of large language models. |
| Outcome: | The proposed method outperforms existing quantization methods with 13.3% boost in MMLU accuracy and 15.5% boost in Wiki perplexity. |