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Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for
  Specialized Cyber Threat Intelligence

Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence

22 July 2022
Markus Bayer
Tobias Frey
Christian A. Reuter
    AAML
ArXivPDFHTML

Papers citing "Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence"

5 / 5 papers shown
Title
CySecBERT: A Domain-Adapted Language Model for the Cybersecurity Domain
CySecBERT: A Domain-Adapted Language Model for the Cybersecurity Domain
Markus Bayer
Philip D. . Kuehn
Ramin Shanehsaz
Christian A. Reuter
13
43
0
06 Dec 2022
FLEX: Unifying Evaluation for Few-Shot NLP
FLEX: Unifying Evaluation for Few-Shot NLP
Jonathan Bragg
Arman Cohan
Kyle Lo
Iz Beltagy
205
104
0
15 Jul 2021
Making Pre-trained Language Models Better Few-shot Learners
Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao
Adam Fisch
Danqi Chen
241
1,919
0
31 Dec 2020
Improving Zero and Few-Shot Abstractive Summarization with Intermediate
  Fine-tuning and Data Augmentation
Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation
Alexander R. Fabbri
Simeng Han
Haoyuan Li
Haoran Li
Marjan Ghazvininejad
Shafiq R. Joty
Dragomir R. Radev
Yashar Mehdad
123
95
0
24 Oct 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural
  Language Inference
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick
Hinrich Schütze
258
1,588
0
21 Jan 2020
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