Text Classification on RCV1

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Rank	Model	Accuracy	Macro F1	Micro F1	P@1	P@3	P@5	nDCG@1	nDCG@3	Paper	Code	Year
1	oh-CNN + two LSTM tv-embed.	92.85	–	–	–	–	–	–	–	Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings		2016
2	HiLAP (bow-CNN)	–	60.1	83.3	–	–	–	–	–	Hierarchical Text Classification with Reinforced Label Assignment	morningmoni/HiLAP	2019
3	MAGNET	–	–	88.5	–	–	–	–	–	MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network	adrinta/MAGNET · akash18tripathi/MAGNET-Multi-Label-Text-Classi-cation-using-Attention-based-Graph-Neural-Network	2020
4	NLP-Cap	–	–	–	97.05	81.27	56.33	97.05	92.47	Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications	andyweizhao/capsule_text_classification · andyweizhao/capsule · andyweizhao/NLP-Capsule · +2	2019
5	oh-CNN + two LSTM tv-embed.	92.85	–	–	–	–	–	–	–	Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings		2016
6	HiLAP (bow-CNN)	–	60.1	83.3	–	–	–	–	–	Hierarchical Text Classification with Reinforced Label Assignment	morningmoni/HiLAP	2019
7	MAGNET	–	–	88.5	–	–	–	–	–	MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network	adrinta/MAGNET · akash18tripathi/MAGNET-Multi-Label-Text-Classi-cation-using-Attention-based-Graph-Neural-Network	2020
8	NLP-Cap	–	–	–	97.05	81.27	56.33	97.05	92.47	Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications	andyweizhao/capsule_text_classification · andyweizhao/capsule · andyweizhao/NLP-Capsule · +2	2019