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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/maexe/linspector-web
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
https://github.com/magic-research/bubogpt
https://github.com/magic282/NeuSum
Neural Document Summarization by Jointly Learning to Score and Select Sentences
https://github.com/mahuiming/TD-LSTM
Effective LSTMs for Target-Dependent Sentiment Classification
https://github.com/maikezuefle/contr-pretraining
GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio
https://github.com/makozi/AfrikaansNMT
Unsupervised Machine Translation Using Monolingual Corpora Only
https://github.com/malllabiisc/RESIDE
Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
https://github.com/mandarjoshi90/triviaqa
TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
https://github.com/mandubian/codenets
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/mangopy/direct-rag-learning
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
https://github.com/mangushev/intent_slot
https://github.com/manshri/tesum
https://github.com/manueldeprada/decoders
https://github.com/manuelladron/Ambiguity-in-Computational-Creativity
https://github.com/maochf/MUSE
Unsupervised Machine Translation Using Monolingual Corpora Only
https://github.com/marekrei/mltagger
https://github.com/marian-nmt/amun
Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions
https://github.com/marinsokol5/Fact-checking
FEVER: a large-scale dataset for Fact Extraction and VERification
https://github.com/mario-holubar/ATCS-InferSent
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
https://github.com/martiansideofthemoon/relic-retrieval
https://github.com/martinomensio/spacy-sentence-bert
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/martinomensio/spacy-universal-sentence-encoder
https://github.com/marvinchung/hw5-textstyletransfer
Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation
https://github.com/matakshay/Neural_Image_Caption_Generator
https://github.com/matken11235/keras-seq2seq
https://github.com/max-planck-innovation-competition/sentence-transformers
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/mayu-ot/hidden-challenges-MR
Uncovering Hidden Challenges in Query-Based Video Moment Retrieval
https://github.com/mayurnewase/Translation
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/maz0318/nlpSummerCamp2019
https://github.com/mbzuai-paris/lm-evaluation-harness-atlas-chat
https://github.com/mcao610/Factual-Error-Correction
Evaluating the Factual Consistency of Abstractive Text Summarization
https://github.com/mcgill-nlp/llm2vec
https://github.com/mcleonard/NLG_Autoencoder
Unsupervised Natural Language Generation with Denoising Autoencoders
https://github.com/meghu2791/DeepLearningModels
Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond
https://github.com/mehrdadyo/Coherent-Language-Generator
Improving Language Generation with Sentence Coherence Objective
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.