Taming Prompt-Based Data Augmentation for Long-Tailed Extreme Multi-Label Text Classification-Reference-Cited by-同舟云学术

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Taming Prompt-Based Data Augmentation for Long-Tailed Extreme Multi-Label Text Classification

Published:2024-04-14 Issue: Volume:21 Page:9981-9985
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
language:
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Author:

Xu Pengyu¹,Song Mingyang¹,Li Ziyi¹,Lu Sijin¹,Jing Liping¹,Yu Jian¹

Affiliation:

1. Beijing Jiaotong University,Beijing Key Lab of Traffic Data Analysis and Mining,Beijing,China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Research and Development

Chinese Academy of Sciences

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446315.pdf?arnumber=10446315

Reference23 articles.

1. Extreme Multi-label Learning for Semantic Matching in Product Search

2. Textual tag recommendation with multi-tag topical attention

3. Triple Alliance Prototype Orthotist Network for Long-Tailed Multi-Label Text Classification

4. Taming Pretrained Transformers for Extreme Multi-label Text Classification

5. Long-tailed Extreme Multi-label Text Classification by the Retrieval of Generated Pseudo Label Descriptions

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