# 論文閱讀

## Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution
### paper
https://arxiv.org/pdf/2109.04712v2.pdf

### code
https://github.com/Roche/BalancedLossNLP

<!-- ## Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets

### paper
https://arxiv.org/pdf/2007.09654.pdf
### code
https://github.com/wutong16/DistributionBalancedLoss

### details
cite 36, ECCV 2020 Spotlight -->

## RMDL: Random Multimodel Deep Learning for Classification
### paper
https://arxiv.org/pdf/1805.01890v2.pdf
### code
https://github.com/kk7nc/RMDL
### details
cite 104, ACM 2018

Ranked #1 on Hierarchical Text Classification of Blurbs (GermEval 2019) on LOCAL DATASET

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## Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications

### paper
https://arxiv.org/pdf/1906.02829v1.pdf
### code
https://github.com/andyweizhao/capsule_text_classification
### details
cite 89, ACL 2019

Ranked #1 on Text Classification on RCV1 (P@1 metric)

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### paper

### code

### details
cite ,
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## Label-Specific Document Representation for Multi-Label Text Classification

### paper
https://aclanthology.org/D19-1044.pdf
### code
https://github.com/EMNLP2019LSAN/LSAN
### details
cite 22, EMNLP 2019

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## Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy Reasoning

### paper
https://arxiv.org/pdf/2104.01666v1.pdf
### code
https://github.com/layneins/Zero-shot-RLHR
### details
cite 3, NAACL 2021

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## Hierarchical Attention Networks for Document Classification

### paper
https://aclanthology.org/N16-1174.pdf

### code
https://github.com/tqtg/hierarchical-attention-networks

### details
cite 3568, NAACL 2016.
https://meetonfriday.com/posts/8cad39eb/ -->