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Language Modeling

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

https://github.com/google-research/google-research/tree/master/enas_lm

Regularizing and Optimizing LSTM Language Models

https://github.com/google-research/human-scene-transformer

Scene Transformer: A unified architecture for predicting multiple agent trajectories

https://github.com/google-research/leaf-audio

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/google-research/lm-extraction-benchmark

The Pile: An 800GB Dataset of Diverse Text for Language Modeling

https://github.com/google/neural-logic-machines

End-To-End Memory Networks

https://github.com/google/paxml

PaLM: Scaling Language Modeling with Pathways

https://github.com/google/seqio

How Much Knowledge Can You Pack Into the Parameters of a Language Model?

https://github.com/gpoesia/peano

Learning Formal Mathematics From Intrinsic Motivation

https://github.com/grammarly/gector

LM-Critic: Language Models for Unsupervised Grammatical Error Correction

https://github.com/grantslatton/llama.cpp

Language Models are Few-Shot Learners

https://github.com/graykode/xlnet-Pytorch

XLNet: Generalized Autoregressive Pretraining for Language Understanding

https://github.com/grayswanai/nanogcg

Query-Based Adversarial Prompt Generation

https://github.com/gregdurrett/nlp-qa-finalproj

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

https://github.com/gregor-ge/mblip

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

https://github.com/gregor160300/federated

Federated Learning for Mobile Keyboard Prediction

https://github.com/gretelai/gretel-synthetics

Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates

https://github.com/griff4692/LMC

Deep contextualized word representations

https://github.com/grtzsohalf/pt.darts

DARTS: Differentiable Architecture Search

https://github.com/gryan12/chat-bot

End-To-End Memory Networks

https://github.com/guidance-ai/guidance

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

https://github.com/guijinSON/MM-Eval

RewardBench: Evaluating Reward Models for Language Modeling

https://github.com/guinmoon/llmfarm

Mirostat: A Neural Text Decoding Algorithm that Directly Controls Perplexity

https://github.com/gujiuxiang/language_cnn_iccv17

An Empirical Study of Language CNN for Image Captioning

https://github.com/guoyaohua/BERT-Chinese-Annotation

Semi-supervised Sequence Learning

https://github.com/guoyongcs/NAT

DARTS: Differentiable Architecture Search

https://github.com/guoyongcs/NATv2

DARTS: Differentiable Architecture Search

https://github.com/guxm2021/MM_ALT

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

https://github.com/guyrosin/temporal_attention

Time Masking for Temporal Language Models

https://github.com/guzhang480/Google_BERT

Semi-supervised Sequence Learning

https://github.com/gychant/CSKMTermDefn

Commonsense Knowledge Mining from Pretrained Models

https://github.com/h4ste/oscar

Semi-supervised Sequence Learning

https://github.com/hackerchenzhuo/LaKo

Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

https://github.com/haewonc/latprotrl

Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space

https://github.com/haianhle/ULMFiT-Sentiment

Universal Language Model Fine-tuning for Text Classification

https://github.com/haidershaour/bert

Semi-supervised Sequence Learning

https://github.com/haisongzhang/roberta-tiny-cased

RoBERTa: A Robustly Optimized BERT Pretraining Approach

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