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

https://github.com/soujanyarbhat/aNswER_multirc

Repurposing Entailment for Multi-Hop Question Answering Tasks

https://github.com/soumik12345/Automatic-Number-Plate-Recognition

Show and Tell: A Neural Image Caption Generator

https://github.com/souvikshanku/digit-captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/souvikshanku/translit-former

Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset

https://github.com/sovit-123/Deep-Learning-Image-Captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/soyoung97/fairseq-gec-korean

Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data

https://github.com/spcl/ncc

Convolutional Neural Networks over Tree Structures for Programming Language Processing

https://github.com/speech-separation-hse/video-features

LipNet: End-to-End Sentence-level Lipreading

https://github.com/speechtranslation/gigas2s

GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio

https://github.com/spider101/visual-semantic-alignments

A Hierarchical Approach for Generating Descriptive Image Paragraphs

https://github.com/sraj-whatdoesthedatasay/Capstone

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

https://github.com/sridharanirudh/tmpFever

FEVER: a large-scale dataset for Fact Extraction and VERification

https://github.com/stair-lab/villm-eval

BERTScore: Evaluating Text Generation with BERT

https://github.com/stanfordnlp/dsp

What Makes Good In-Context Examples for GPT-$3$?

https://github.com/starry91/NMT-Lab

Sequence to Sequence Learning with Neural Networks

https://github.com/stikbuf/Language_Modeling

Language Modeling with Gated Convolutional Networks

https://github.com/stillarrow/S2VT_ACT

Sequence to Sequence -- Video to Text

https://github.com/stingram/CV_Image_Captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/stoensin/IC

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

https://github.com/stoplime/OpenAudioAI

Hierarchical RNN with Static Sentence-Level Attention for Text-Based Speaker Change Detection

https://github.com/studian/CVND_P2_Image_Captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/styfeng/tinydialogues

Visual Grounding Helps Learn Word Meanings in Low-Data Regimes

https://github.com/suakow/mcan-vqa-thai

WangchanBERTa: Pretraining transformer-based Thai Language Models

https://github.com/subhamdas226/Chatbot

A Neural Conversational Model

https://github.com/sudatta0993/Dynamic-Congestion-Prediction

Top-down Visual Saliency Guided by Captions

https://github.com/sulcantonin/text_icalepcs23

SimCSE: Simple Contrastive Learning of Sentence Embeddings

https://github.com/sumehta/bilstm_crf_extract

Bidirectional LSTM-CRF Models for Sequence Tagging

https://github.com/sunnysinghnitb/text-corrector-software

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/sunnysinghnitb/text_corrector_software

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/sunsiqi26/Entailment-with-TensorFlow

ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

https://github.com/supreethub/Image-Captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/suryachintu/Quora-Insincere-Questions-Kaggle

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/sustcsonglin/TN-PCFG

Compound Probabilistic Context-Free Grammars for Grammar Induction

https://github.com/svjan5/CNN-for-text-classification

Convolutional Neural Networks for Sentence Classification

https://github.com/sxjscience/GluonNLP-Slot-Filling

BERT for Joint Intent Classification and Slot Filling

https://github.com/tai314159/pwibm-putting-words-in-bert-s-mouth

Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowords

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