Papers with Code 아카이브

Language Modeling

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

https://github.com/THUDM/KOBE

The Curious Case of Neural Text Degeneration

https://github.com/THUcqb/KOBE

The Curious Case of Neural Text Degeneration

https://github.com/TJUIRLAB/AAAI19-TSLM

A Generalized Language Model in Tensor Space

https://github.com/TJUIRLAB/CIKM2018_QMWFLM

A Quantum Many-body Wave Function Inspired Language Modeling Approach

https://github.com/TSLNIHAOGIT/bert

Semi-supervised Sequence Learning

https://github.com/TSLNIHAOGIT/bert_run

Semi-supervised Sequence Learning

https://github.com/TTTTTTris/wandaplus

Wanda++: Pruning Large Language Models via Regional Gradients

https://github.com/TU2021/DPO-VP

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

https://github.com/TYTYTYTYTYTYTYTYTY/558-project

Semi-supervised Sequence Learning

https://github.com/TaiseiAso/BiGruAttEncDec

The Curious Case of Neural Text Degeneration

https://github.com/TamSiuhin/Per-Pcs

LaMP: When Large Language Models Meet Personalization

https://github.com/TangJiaLong/Knowledge-Projection-for-ERE

A Surprisingly Robust Trick for Winograd Schema Challenge

https://github.com/TeaPoly/Conformer-Athena

Conformer: Convolution-augmented Transformer for Speech Recognition

https://github.com/TeddLi/Further-manually-annotated-glockner

Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language Inference

https://github.com/TejInaco/multimodalML

Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text

https://github.com/Tencent/TurboTransformers

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/TensorSpeech/TensorFlowASR

Jasper: An End-to-End Convolutional Neural Acoustic Model

https://github.com/Tetsuya-Nishikawa/ConvLSTM_DEMO

Recurrent Batch Normalization

https://github.com/TheShadow29/subreddit-classification-dataset

Universal Language Model Fine-tuning for Text Classification

https://github.com/TheophileBlard/french-sentiment-analysis-with-bert

MultiFiT: Efficient Multi-lingual Language Model Fine-tuning

https://github.com/ThilinaRajapakse/simpletransformers

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

https://github.com/TianduoWang/MsAT

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

https://github.com/TieDanCuihua/Hierarchical-Attention-Networks-for-Document-Classification-Tensorflow

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

https://github.com/TieDanCuihua/ORDERED-NEURONS-INTEGRATING-TREE-STRUCTURES-INTO-RECURRENT-NEURAL-NETWORKS--tensorflow

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

https://github.com/Tikquuss/meta_XLM

Cross-lingual Language Model Pretraining

https://github.com/TimDettmers/transformer-xl

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

https://github.com/Tobias-K93/media-bias-prediction

Single Headed Attention RNN: Stop Thinking With Your Head

https://github.com/TobiasNorlund/flashback-gpt

Building a Swedish Open-Domain Conversational Language Model

https://github.com/TommyWongww/MemoryNetworks

End-To-End Memory Networks

https://github.com/Tony-Y/pytorch_warmup

On the Variance of the Adaptive Learning Rate and Beyond

https://github.com/TonyX19/bert_hyperpartisan

Semi-supervised Sequence Learning

https://github.com/TooTouch/SPARTA

Hybrid Ranking Network for Text-to-SQL

https://github.com/TreeLimes/QANAS

Neural Architecture Search with Reinforcement Learning

https://github.com/TrentBrick/PyTorchDiscreteFlows

Discrete Flows: Invertible Generative Models of Discrete Data

https://github.com/TsingZ0/FL-IoT

Federated Evaluation of On-device Personalization

https://github.com/UIC-Liu-Lab/ContinualLM

Adapting a Language Model While Preserving its General Knowledge

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