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

https://github.com/onehaitao/R-BERT-relation-extraction

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

https://github.com/open-finance-lab/finlora

BERTScore: Evaluating Text Generation with BERT

https://github.com/open-mmlab/mmclassification

Transformer in Transformer

https://github.com/openbiolink/promptsource

Language Models are Few-Shot Learners

https://github.com/opencog/link-grammar

The Annotation Guideline of LST20 Corpus

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

Language Models are Few-Shot Learners

https://github.com/oroszgy/spacy-hungarian-models

Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines

https://github.com/oto-labs/librarian

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/outcastofmusic/quick-nlp

A Neural Conversational Model

https://github.com/ovbystrova/InstructionNER

InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NER

https://github.com/p208p2002/Sentence-BERT-mean-operation

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/paddorch/SelfAttnSent.paddle

A Structured Self-attentive Sentence Embedding

https://github.com/paper-cat/Sentence-Classifications

Convolutional Neural Networks for Sentence Classification

https://github.com/parajain/data-to-text

Neural Text Generation from Structured Data with Application to the Biography Domain

https://github.com/parajain/structscribe

Scalable Micro-planned Generation of Discourse from Structured Data

https://github.com/pathway/crosslang_embed

Universal Sentence Encoder

https://github.com/paulagarciamolina/qnlp_qiskit_hackathon

QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer

https://github.com/paulsens/ConvNeur

A Neural Conversational Model

https://github.com/pbcquoc/transformer

Effective Approaches to Attention-based Neural Machine Translation

https://github.com/pcyin/pytorch_basic_nmt

Effective Approaches to Attention-based Neural Machine Translation

https://github.com/pedrodke/libris2s

LibriVoxDeEn: A Corpus for German-to-English Speech Translation and German Speech Recognition

https://github.com/peithous/pytorch-BinClass-intro

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

https://github.com/pencoa/state-lstm

N-ary Relation Extraction using Graph State LSTM

https://github.com/percent4/RoBERTa_and_DCMN_plus_for_RACE

DCMN+: Dual Co-Matching Network for Multi-choice Reading Comprehension

https://github.com/perceptiveshawty/RankCSE

RankCSE: Unsupervised Sentence Representations Learning via Learning to Rank

https://github.com/peteanderson80/coco-caption

CIDEr: Consensus-based Image Description Evaluation

https://github.com/phamnam-mta/ConveRT-PolyAI-Vietnamese

ConveRT: Efficient and Accurate Conversational Representations from Transformers

https://github.com/phanxuanphucnd/Felix

Felix: Flexible Text Editing Through Tagging and Insertion

https://github.com/philipperemy/keras-attention-mechanism

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/phnk/D7047E

Visualizing and Understanding Neural Models in NLP

https://github.com/pipidog/CNLP

Convolutional Neural Networks for Sentence Classification

https://github.com/pipidog/QNLP

Convolutional Neural Networks for Sentence Classification

https://github.com/piyush2896/CNN-Text-Classifier

Convolutional Neural Networks for Sentence Classification

https://github.com/piyushmakhija5/hinglishnorm

hinglishNorm -- A Corpus of Hindi-English Code Mixed Sentences for Text Normalization

https://github.com/piyushmakhija5/normalizationdataset

hinglishNorm -- A Corpus of Hindi-English Code Mixed Sentences for Text Normalization

https://github.com/pjenpoomjai/LipNet

LipNet: End-to-End Sentence-level Lipreading

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