Papers with Code 아카이브
Natural Language Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 6
- 보존된 평가 기록
- 42
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/enhuiz/transformer-pytorch
https://github.com/enod/arxiv-nlp-notes
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epcpu/deep-nlp-links
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epfl-nlp/kogito
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs
https://github.com/epfml/collaborative-attention
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/eps696/aphantasia
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/ericperfect/Bert_Position_BiLSTM_Attention_CRF_LSTMDecoder
https://github.com/ericyinyzy/vlattack
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/esteng/calibration_miso
https://github.com/ethancaballero/neural-engineers-first-attempt
https://github.com/eunseo1092/Graduation_project
https://github.com/evtaktasheva/dependency_extraction
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ewdowiak/Sicilian_Translator
https://github.com/exa-labs/exa-mcp-server
https://github.com/expertailab/spaceqa
https://github.com/extensive-nlp/TSAI-DeepNLP-END2.0
https://github.com/fabiocorreacordeiro/Elsevier_abstracts-Classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/facebookresearch/InferSent
DisSent: Sentence Representation Learning from Explicit Discourse Relations
https://github.com/facebookresearch/MLQA
https://github.com/facebookresearch/SentEval
DisSent: Sentence Representation Learning from Explicit Discourse Relations
https://github.com/facebookresearch/UnsupervisedMT
https://github.com/facebookresearch/XLM
https://github.com/facebookresearch/brainmagick
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/facebookresearch/clip-rocket
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/facebookresearch/data2vec_vision
Unified Language Model Pre-training for Natural Language Understanding and Generation
https://github.com/facebookresearch/fairseq
https://github.com/facebookresearch/lingua
DataComp-LM: In search of the next generation of training sets for language models
https://github.com/facebookresearch/multihop_dense_retrieval
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
https://github.com/facebookresearch/vissl
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/facebookresearch/xformers
https://github.com/faizansuhail89/bert
https://github.com/fanchenyou/transformer-study
https://github.com/fancyerii/bert
https://github.com/farizrahman4u/seq2seq
https://github.com/fastscience-ai/medflamingo
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.