https://github.com/KevinYoung98/Seq2Seq-PyTorch
Effective Approaches to Attention-based Neural Machine Translation
Papers with Code 아카이브
Sentence
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/KhenAharon/Deep-Learning-SNLI-Residual-Stacked-Encoders
Shortcut-Stacked Sentence Encoders for Multi-Domain Inference
https://github.com/KifayatMsd/C-LSTM-text-classification
https://github.com/Kim-inhwan/Word2vec-CNN-for-classfication
https://github.com/KnightZhang625/BERT_TF
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/KyGao/token-level-classification
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
https://github.com/Kyfafyd/MirrorGAN
MirrorGAN: Learning Text-to-image Generation by Redescription
https://github.com/Kyubyong/word2word
word2word: A Collection of Bilingual Lexicons for 3,564 Language Pairs
https://github.com/LAL-project/treebank-parser
https://github.com/LFavano/Automated-Fact-Checking-System
https://github.com/LahiruSen/S-LSTM_Sinhala
https://github.com/LawrenceDuan/myLASER
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
https://github.com/Layne-Huang/EGFI
https://github.com/LazarusNLP/NusaBERT
IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding
https://github.com/LeeSureman/Batch_Parallel_LatticeLSTM
https://github.com/Lemoners/Attention-Is-All-You-Need
https://github.com/Leputa/CIKM-AnalytiCup-2018
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
https://github.com/LiZhenghua0311/lip
https://github.com/LiamMaclean216/Pytorch-Transfomer
Context-based Transformer Models for Answer Sentence Selection
https://github.com/Lieberk/Paddle-AoA-Captioning
Deep Visual-Semantic Alignments for Generating Image Descriptions
https://github.com/Linear95/BinarySentEmb
Learning Compressed Sentence Representations for On-Device Text Processing
https://github.com/LisaAnne/DCC
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
https://github.com/LisaAnne/Hallucination
https://github.com/LitianD/Joint_RE
A Novel Cascade Binary Tagging Framework for Relational Triple Extraction
https://github.com/Liut2016/stackedResBiLSTM
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/LorenzoAgnolucci/BERT_for_ABSA
Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence
https://github.com/LucaMaurici/MultiHop-Reading-Comprehension-DRL
Multi-hop Reading Comprehension via Deep Reinforcement Learning based Document Traversal
https://github.com/M-S-ALAM/Sarcastic-Comment-Detection
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks
https://github.com/MFajcik/RumourEval2019
https://github.com/MINGG2333/bert_ms
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
https://github.com/MJ-Jang/Paraphrase-Thought
Paraphrase Thought: Sentence Embedding Module Imitating Human Language Recognition
https://github.com/MJ-Jang/RNN_SVAE
Recurrent Neural Network-Based Semantic Variational Autoencoder for Sequence-to-Sequence Learning
https://github.com/MS-Mind/MS-Code-01/tree/main/seq2seq
Lossless Acceleration for Seq2seq Generation with Aggressive Decoding
https://github.com/MS-Mind/MS-Code-01/tree/main/textcnn
https://github.com/Maab-Nimir/Neural-Machine-Translation-by-Jointly-Learning-to-Align-and-Translate
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/MahmoudWahdan/dialog-nlu
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.