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/yueyongjiao/attention_is_all_you_need_pytorch
https://github.com/yuhangT/tf_bert
https://github.com/yujiabao/ls
https://github.com/yumoh/speech-keras
https://github.com/yushi-y/dpo-toxic-neurons
https://github.com/yuuun/clip_pytorch
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/yxuansu/Chinese-TaCL-BERT-NER-CWS
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
https://github.com/yydai/bert_test
https://github.com/yyht/Conv_Bert
ConvBERT: Improving BERT with Span-based Dynamic Convolution
https://github.com/zaaztt/bert_chinese_example
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/zankner/Transformer
https://github.com/zapplea/bert
https://github.com/zaradana/Fast_BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/zehuiwu/SpeechCueLLM
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances
https://github.com/zer0sh0t/artificial_intelligence/tree/master/language_models/bidirectional_encoder_representations_from_transformers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/zer0sh0t/artificial_intelligence/tree/master/transformer
https://github.com/zhang-huihui/git-repository
https://github.com/zhangbo2008/best_pytorch_transformer
https://github.com/zhangxu0963/npc
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/zhengcj1/ChID-Dataset
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/zhoucz97/JointBERT-paddle
https://github.com/zhuzhicai/SQuAD2.0-Baseline-Test-with-BiDAF-No-Answer
https://github.com/zipeiyang/DeepSpeechRecognition
https://github.com/zliucr/coach
https://github.com/zsweet/BERT_zsw
https://github.com/zysite/post
https://gitlab.com/birder/birder
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
https://huggingface.co/google/roberta2roberta_L-24_wikisplit
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.