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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/danieljf24/hybrid_space

Dual Encoding for Video Retrieval by Text

https://github.com/danifg/SyntacticPointer

Stack-Pointer Networks for Dependency Parsing

https://github.com/daniilrobnikov/vits2

NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality

https://github.com/danilo-dessi/skg

Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

https://github.com/daniter-cu/DiscoEval

Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations

https://github.com/dantetam/twitterServerAuth

Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features

https://github.com/daphne12345/SummarizationRadiologyReports

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/daqingliu/CAVP

Context-Aware Visual Policy Network for Fine-Grained Image Captioning

https://github.com/daqingliu/coco-caption

CIDEr: Consensus-based Image Description Evaluation

https://github.com/dashayushman/TAC-GAN

Skip-Thought Vectors

https://github.com/dataflowr/self-attentive-sentence-embedding

A Structured Self-attentive Sentence Embedding

https://github.com/datalogue/keras-attention

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/datcancode/sentence-transformers

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/daveredrum/ScanRefer

ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language

https://github.com/davidalami/convert

ConveRT: Efficient and Accurate Conversational Representations from Transformers

https://github.com/davide97l/Sentiment-analysis

Convolutional Neural Networks with Recurrent Neural Filters

https://github.com/davidgolub/charizard

Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer

https://github.com/davidsvaughn/dts-tf

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

https://github.com/ddajing/multilayer-cnn-text-classification

Convolutional Neural Networks for Sentence Classification

https://github.com/declare-lab/hyperred

RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction

https://github.com/deepsense-ai/unblackboxing_webinar

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/delldu/TextCNN

Convolutional Neural Networks for Sentence Classification

https://github.com/dengyang17/dengyang17.github.io

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering

https://github.com/denizyuret/fastsubs-googlecode

FASTSUBS: An Efficient and Exact Procedure for Finding the Most Likely Lexical Substitutes Based on an N-gram Language Model

https://github.com/dennlinger/summaries

SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents

https://github.com/dennybritz/cnn-text-classification-tf

Convolutional Neural Networks for Sentence Classification

https://github.com/determined22/zh-ner-tf

Bidirectional LSTM-CRF Models for Sequence Tagging

https://github.com/deterministic-algorithms-lab/Large-XLM

Phrase-Based & Neural Unsupervised Machine Translation

https://github.com/dewanderelex/LanguageTranslation

Sequence to Sequence Learning with Neural Networks

https://github.com/dgonzalez-ri/neural-visual-storyteller

Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge

https://github.com/dhesenkamp/attentive-lstm

A Structured Self-attentive Sentence Embedding

https://github.com/dhruvdcoder/sparse-structured-attention

A Regularized Framework for Sparse and Structured Neural Attention

https://github.com/diana-hep/treenin

QCD-Aware Recursive Neural Networks for Jet Physics

https://github.com/dianaglzrico/neural-visual-storyteller

Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge

https://github.com/diegoschapira/CNN-Text-Classifier-using-Keras

Convolutional Neural Networks for Sentence Classification

https://github.com/diffbot/knowledge-net

Entity, Relation, and Event Extraction with Contextualized Span Representations

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.