Papers by Yifu Sun

2 papers
Contextual Text Denoising with Masked Language Model (D19-55)

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Challenge: Recent advances in NLP have been vulnerable to noisy inputs.
Approach: They propose a contextual text denoising algorithm based on a ready-to-use masked language model that does not require retraining and can be integrated into any NLP system without additional training on paired cleaning training data.
Outcome: The proposed algorithm can correct noise text and improve performance in several downstream tasks.
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs (2023.emnlp-main)

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Challenge: Recent work has shown that large language models are superior to conventional methods in various tasks.
Approach: They propose a data-independent quantization algorithm that leaves outliers in the weight and quantization ranges . they find the algorithm runs over 10 times faster than the data-dependent methods .
Outcome: The proposed method runs over 10 times faster than the data-dependent methods.

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