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

https://github.com/jerryyli/valhalla-nmt

VALHALLA: Visual Hallucination for Machine Translation

https://github.com/jiachangliu/kategpt3

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

https://github.com/jiacheng-xu/vmf_vae_nlp

Generating Sentences by Editing Prototypes

https://github.com/jiajunhua/facebookresearch-MUSE

Unsupervised Machine Translation Using Monolingual Corpora Only

https://github.com/jiamingkong/infoxlm_paddle

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/jiangnanhugo/seq2seq_cuda

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/jiaruncao/BioCopyMechanism

Sequential Copying Networks

https://github.com/jidasheng/bi-lstm-crf

Bidirectional LSTM-CRF Models for Sequence Tagging

https://github.com/jimmyyfeng/TD-LSTM

Effective LSTMs for Target-Dependent Sentiment Classification

https://github.com/jingyuanz/keras-self-attention-layer

A Structured Self-attentive Sentence Embedding

https://github.com/jingyuanz/telecom_query_classification

A C-LSTM Neural Network for Text Classification

https://github.com/jishubasak/Punny-Caption--Exploring-Image-Captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/jiweil/Hierarchical-Neural-Autoencoder

A Hierarchical Neural Autoencoder for Paragraphs and Documents

https://github.com/jjessyli/speciteller

Domain Agnostic Real-Valued Specificity Prediction

https://github.com/jklafka/noisy-nets

Sequence to Sequence Learning with Neural Networks

https://github.com/jmhessel/pycocoevalcap

CIDEr: Consensus-based Image Description Evaluation

https://github.com/jmpu/deepfaketextdetection

Neural Deepfake Detection with Factual Structure of Text

https://github.com/jmtomczak/vae_householder_flow

Generating Sentences from a Continuous Space

https://github.com/jmyrberg/finnlem

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/joaodsmarques/lumberchunker

Dense X Retrieval: What Retrieval Granularity Should We Use?

https://github.com/jobdataexchange/competensor

Universal Sentence Encoder

https://github.com/joelniklaus/lawinstruct

Resolving Legalese: A Multilingual Exploration of Negation Scope Resolution in Legal Documents

https://github.com/joelweber97/Python3_TF_Certificate

PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts

https://github.com/johnnyb1509/2020_VBDI_DL

Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting

https://github.com/jonas-becker/text-generation

BERTScore: Evaluating Text Generation with BERT

https://github.com/jordiclive/Convert-PolyAI-Torch

ConveRT: Efficient and Accurate Conversational Representations from Transformers

https://github.com/joseewei/wenet

Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recognition

https://github.com/josefigueroa168/NLP-project

AMR Parsing as Graph Prediction with Latent Alignment

https://github.com/joseph-bongo-220/TV_NLP_Project

Universal Sentence Encoder

https://github.com/joshuaczhao/CNN-Sentence-Classifier-Reproduction

A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

https://github.com/jpablou/Matching-The-Blanks-Ths

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

https://github.com/jules-samaran/vl-bert

VL-BERT: Pre-training of Generic Visual-Linguistic Representations

https://github.com/juletx/image-caption-generation

Show and Tell: A Neural Image Caption Generator

https://github.com/juletx/lm-evaluation-harness

Language Models are Few-Shot Learners

https://github.com/junfenglx/reasoning_attention

Learning Natural Language Inference with LSTM

https://github.com/junronglau/CS421_Project

Siamese CBOW: Optimizing Word Embeddings for Sentence Representations

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