Papers with Code 아카이브
Natural Language Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Natural Language Understanding is an important field of Natural Language Processing which contains various tasks such as text classification, natural language inference and story comprehension. Applications enabled by natural language understanding range from question answering to automated reasoning.
Source: Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/paolanu/BERT_epitope
https://github.com/parcorelab/comscribe
https://github.com/patrickhart/jaxdl
https://github.com/paulsens/ConvNeur
https://github.com/paulskeie/stadnamn
https://github.com/payalmohapatra/Multimodal-Speech-Disfluency
https://github.com/pengming617/bert_classification
https://github.com/pengshuyuan/Bert
https://github.com/penny9287/sockeye
https://github.com/pennylaneai/generative-quantum-states
https://github.com/peterwestai2/symbolic-knowledge-distillation
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs
https://github.com/pfecht/bert-exploration
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/philschmid/knowledge-distillation-transformers-pytorch-sagemaker
FastFormers: Highly Efficient Transformer Models for Natural Language Understanding
https://github.com/phohenecker/pytorch-transformer
https://github.com/phueb/BabyBertSRL
Multi-Task Deep Neural Networks for Natural Language Understanding
https://github.com/phueb/CHILDES-SRL
Multi-Task Deep Neural Networks for Natural Language Understanding
https://github.com/piegu/language-models
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/pingheng001/Cnn-Bert
https://github.com/piquil/rydberggpt
https://github.com/pisalore/roberta_results
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/plkmo/Transformer-Eng2French
https://github.com/pluslabnlp/cluster
Identifying Distributional Perspective Differences from Colingual Groups
https://github.com/poethan/cushLEPOR
Translation Quality Assessment: A Brief Survey on Manual and Automatic Methods
https://github.com/polzinben/TensorFlow_NLP
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/pomonam/AttentionCluster
https://github.com/prabhupad26/100daysofML
https://github.com/pritam1322/Machine-Translation-with-Transformer
https://github.com/probcomp/sppl
https://github.com/protagolabs/odyssey-math
https://github.com/ps2811/Bert-Multi-Label-Text-Classification-GitVersion
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/pseulki/rococo
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/pswietojanski/slurp
https://github.com/pwc-1/Paper-10/tree/main/tinybert
TinyBERT: Distilling BERT for Natural Language Understanding
https://github.com/pwc-1/Paper-5/tree/main/moss
MOSS: End-to-End Dialog System Framework with Modular Supervision
https://github.com/pwc-1/Paper-8/tree/main/clip
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.