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Document Classification

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Document Classification is a procedure of assigning one or more labels to a document from a predetermined set of labels.

Source: Long-length Legal Document Classification

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/longdt219/xlingualemb

Learning Crosslingual Word Embeddings without Bilingual Corpora

https://github.com/lucidrains/block-recurrent-transformer-pytorch

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

https://github.com/lucidrains/flash-cosine-sim-attention

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

https://github.com/lucidrains/sinkhorn-transformer

Sparse Sinkhorn Attention

https://github.com/lukecavabarrett/pna

Graph Attention Networks

https://github.com/lukexyz/Language-Models

MultiFiT: Efficient Multi-lingual Language Model Fine-tuning

https://github.com/mahendrathapa/graph-convolution-network

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/mahequn001/graphlearning/tree/master/model_zoo/gcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/mahsa91/GKD

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/mahsa91/RA-GCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/marble0117/GNN_models_pytorch

Graph Attention Networks

https://github.com/marble0117/GNN_models_pytorch_geometric

Graph Attention Networks

https://github.com/marblet/GNN_models_pytorch_geometric

Graph Attention Networks

https://github.com/marblet/gat-pytorch

Graph Attention Networks

https://github.com/masukislam/DS8008_NLP

Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles

https://github.com/meliketoy/graph-cnn.pytorch

Revisiting Semi-Supervised Learning with Graph Embeddings

https://github.com/microsoft/chunk-attention

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

https://github.com/microsoft/unilm/tree/master/layoutlm

Modular Multimodal Architecture for Document Classification

https://github.com/mindspore-ai/models/tree/master/official/gnn/gat

Graph Attention Networks

https://github.com/mipot101/GNM-Implementations

Revisiting Semi-Supervised Learning with Graph Embeddings

https://github.com/mitya8128/experiments_notes

Graph Attention Networks

https://github.com/mleimeister/document-image-classification

Multimodal deep networks for text and image-based document classification

https://github.com/mlzxzhou/keras-gnm

Graph Attention Networks

https://github.com/n-waves/multifit

A Corpus for Multilingual Document Classification in Eight Languages

https://github.com/negarhdr/PGCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/nieci2024/pyglcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/ninoxjy/graph-embedding

DeepWalk: Online Learning of Social Representations

https://github.com/nnaakkaaii/g2-MLP

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/noahtren/Graph-Attention-Networks-TensorFlow-2

Graph Attention Networks

https://github.com/nyk510/scdv-python

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

https://github.com/oj9040/GraphSAGE_RL

DeepWalk: Online Learning of Social Representations

https://github.com/ondrejba/tf_calibrate

On Calibration of Modern Neural Networks

https://github.com/p-lambda/verified_calibration

On Calibration of Modern Neural Networks

https://github.com/pengsl-lab/mssl

Graph Attention Networks

https://github.com/pengsl-lab/mssl2drug

Graph Attention Networks

https://github.com/phanein/deepwalk

DeepWalk: Online Learning of Social Representations

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