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20212023
most citedMemorization in NLP Fine-tuning Methods

11 citations · 35 across the 12 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CL2022

Non-Parametric Temporal Adaptation for Social Media Topic Classification

Fatemehsadat Mireshghallah, Nikolai Vogler, Junxian He +3

User-generated social media data is constantly changing as new trends influence online discussion and personal information is deleted due to privacy concerns. However, most current…

cs.CL2022★ 11 cited

Memorization in NLP Fine-tuning Methods

Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang +2

Large language models are shown to present privacy risks through memorization of training data, and several recent works have studied such risks for the pre-training phase. Little…

cs.CL2022★ 2 cited

Mix and Match: Learning-free Controllable Text Generation using Energy Language Models

Fatemehsadat Mireshghallah, Kartik Goyal, Taylor Berg-Kirkpatrick

Recent work on controlled text generation has either required attribute-based fine-tuning of the base language model (LM), or has restricted the parameterization of the attribute d…

cs.LG2022★ 10 cited

Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks

Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal +2

The wide adoption and application of Masked language models~(MLMs) on sensitive data (from legal to medical) necessitates a thorough quantitative investigation into their privacy v…

cs.CL2022★ 1 cited

An Unsupervised Masking Objective for Abstractive Multi-Document News Summarization

Nikolai Vogler, Songlin Li, Yujie Xu +2

We show that a simple unsupervised masking objective can approach near supervised performance on abstractive multi-document news summarization. Our method trains a state-of-the-art…