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Document Classification

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하위 태스크: 1
평가표: 22
보존된 평가 기록: 51

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/gordicaleksa/pytorch-GAT

Graph Attention Networks

https://github.com/goyalanil/Multiview_Dataset_MNIST

Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization

https://github.com/handasontam/GAT-with-edgewise-attention

Graph Attention Networks

https://github.com/hazdzz/GCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/hazyresearch/flash-attention

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

https://github.com/helenabalabin/covid-19-document-classification

DocBERT: BERT for Document Classification

https://github.com/helmy-elrais/RoBERT_Recurrence_over_BERT

Hierarchical Transformers for Long Document Classification

https://github.com/heraclex12/VLSP2020-Fake-News-Detection

Hierarchical Transformers for Long Document Classification

https://github.com/hle027/IR-Competition

SPECTER: Document-level Representation Learning using Citation-informed Transformers

https://github.com/hollance/reliability-diagrams

On Calibration of Modern Neural Networks

https://github.com/huggingface/transformers

BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining

https://github.com/iMoonLab/DHGNN

Revisiting Semi-Supervised Learning with Graph Embeddings

https://github.com/iamarjunchandra/LayoutLM-Form-Understanding---Sequence-Labeling

Modular Multimodal Architecture for Document Classification

https://github.com/idiap/gile

Multilingual Hierarchical Attention Networks for Document Classification

https://github.com/imamathcat/LASER_Dependencies

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/imran3180/pytorch-nli

Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News

https://github.com/isotlaboratory/ml4vrp

Graph Attention Networks

https://github.com/javiferran/document-classification

Improving accuracy and speeding up Document Image Classification through parallel systems

https://github.com/jeongukjae/smaller-labse

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/jiamingkong/infoxlm_paddle

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/jiangboahu/glcn-tf

Revisiting Semi-Supervised Learning with Graph Embeddings

https://github.com/jmribeiro/Pruning-and-Sparsemax-Methods-for-Hierarchical-Attention-Networks

Pruning and Sparsemax Methods for Hierarchical Attention Networks

https://github.com/joaopedromattos/gnee

Graph Attention Networks

https://github.com/johntd54/stanford_car

On Calibration of Modern Neural Networks

https://github.com/karlmoritz/bicvm

Multilingual Distributed Representations without Word Alignment

https://github.com/kiharalab/gnn_pocket

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/kimiyoung/planetoid

Revisiting Semi-Supervised Learning with Graph Embeddings

https://github.com/kmamykin/askamanager_salary_survey

Towards a Job Title Classification System

https://github.com/kmkwon94/ainize-laser

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/knowlab/bi-weekly-paper-presentation

Unsupervised Document Embedding via Contrastive Augmentation

https://github.com/labmlai/annotated_deep_learning_paper_implementations

Graph Attention Networks

https://github.com/lackel/hierarchical_weighted_scl

HDLTex: Hierarchical Deep Learning for Text Classification

https://github.com/latkins/trifast

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

https://github.com/leihuayi/NetworkEmbedding

DeepWalk: Online Learning of Social Representations

https://github.com/lipingcoding/pygcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/liu6zijian/simplified-gcn-model

Graph Attention Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.