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

https://github.com/chalothon/Sentence2Vec

Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features

https://github.com/chalothon/Skip-Thought

Skip-Thought Vectors

https://github.com/chao-ji/tf-seq2seq

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/charles9n/bert-sklearn

SciBERT: A Pretrained Language Model for Scientific Text

https://github.com/cheng18/bilm-tf

Evaluation of sentence embeddings in downstream and linguistic probing tasks

https://github.com/chenjoya/2dtan

Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language

https://github.com/chenxinpeng/im2p

A Hierarchical Approach for Generating Descriptive Image Paragraphs

https://github.com/chesterdu/contrastive_summary

Text Summarization with Pretrained Encoders

https://github.com/chielingyueh/anaphora_resolution_chemical_patents

Enriching Pre-trained Language Model with Entity Information for Relation Classification

https://github.com/chiemenz/AzureML-Sentiment-Classification-and-Model-Deployment

Convolutional Neural Networks for Sentence Classification

https://github.com/chiemenz/automl_vs_hyperdrive

Convolutional Neural Networks for Sentence Classification

https://github.com/chijames/Poly-Encoder

Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring

https://github.com/chijames/gst

ListOps: A Diagnostic Dataset for Latent Tree Learning

https://github.com/chldydgh4687/2020-1.VideoCaptioning

Reconstruction Network for Video Captioning

https://github.com/chncwang/InsNet

Cue-word Driven Neural Response Generation with a Shrinking Vocabulary

https://github.com/chodi150/scanrefer-pointgroup

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

https://github.com/chojc408/Dynamic-CNN-using-Global_k_MaxPooling1D

A Convolutional Neural Network for Modelling Sentences

https://github.com/chris4540/DD2430-ds-proj

Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

https://github.com/chrisc36/debias

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

https://github.com/christian3141/blonde

BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation

https://github.com/chun5212021202/ACM-Net

Query-based Attention CNN for Text Similarity Map

https://github.com/chunghyunhee/twitter_disaster_NLP

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/chunlei2/show-and-tell

Show and Tell: A Neural Image Caption Generator

https://github.com/cipnlu/InformationExtraction

Relation Extraction : A Survey

https://github.com/cjyanyi/CS542-tweets-sentiment-analysis

Convolutional Neural Networks for Sentence Classification

https://github.com/clementgr/sentiment-analysis

Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts

https://github.com/climsocana/tecb-de

TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

https://github.com/clip-vil/cider

CIDEr: Consensus-based Image Description Evaluation

https://github.com/clmbrs/communication-translation

Multilingual Denoising Pre-training for Neural Machine Translation

https://github.com/cluebbers/dpo-rlhf-paraphrase-types

Towards Human Understanding of Paraphrase Types in ChatGPT

https://github.com/cluebenchmark/simclue

SimCSE: Simple Contrastive Learning of Sentence Embeddings

https://github.com/clutr/clutr

Generating Sentences from a Continuous Space

https://github.com/cmasch/cnn-text-classification

Convolutional Neural Networks for Sentence Classification

https://github.com/codectr/RefineCTR/blob/main/FRCTR/module_zoo/contextnet.py

ContextNet: A Click-Through Rate Prediction Framework Using Contextual information to Refine Feature Embedding

https://github.com/codedotal/gpt-code-clippy

Language Models are Few-Shot Learners

https://github.com/codegram/calbert

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

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