Mitigating Unintended Memorization in Language Models Via Alternating Teaching-Reference-Cited by-同舟云学术

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Mitigating Unintended Memorization in Language Models Via Alternating Teaching

Published:2023-06-04 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Liu Zhe¹,Zhang Xuedong¹,Peng Fuchun¹

Affiliation:

1. Meta AI,Menlo Park,CA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10094559/10094560/10096557.pdf?arnumber=10096557

Reference25 articles.

1. Semi-supervised knowledge transfer for deep learning from private training data;papernot;Proc ICLR,2017

2. Librispeech: An ASR corpus based on public domain audio books

3. SeqPATE: Differentially private text generation via knowledge distillation;tian,2022

4. Scalable private learning with PATE;papernot;Proc ICLR,2018

5. Quantifying memorization across neural language models;carlini,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Forgetting Private Textual Sequences in Language Models Via Leave-One-Out Ensemble;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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