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/MS-P3/code6/tree/main/rag

RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

https://github.com/MS-P3/code7/tree/main/vision_text_dual_encoder

Encoder vs Decoder: Comparative Analysis of Encoder and Decoder Language Models on Multilingual NLU Tasks

https://github.com/MS-P3/code7/tree/main/visual_bert

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

https://github.com/MS-P3/code7/tree/main/x_clip

ClipCap: CLIP Prefix for Image Captioning

https://github.com/MS-P3/code7/tree/main/xlm

Cross-lingual Language Model Pretraining

https://github.com/MS-P3/code7/tree/main/xlm_roberta

Cross-lingual Language Model Pretraining

https://github.com/MS-P3/code7/tree/main/xlm_roberta_xl

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/MS-P3/code7/tree/main/xlnet

XLNet: Generalized Autoregressive Pretraining for Language Understanding

https://github.com/MS-P3/code7/tree/main/xmod

Xmodel-LM Technical Report

https://github.com/MaZhiyuanBUAA/bert-tf1.4.0

Semi-supervised Sequence Learning

https://github.com/MagicHub-io/Magic-Data-ASR-SD-Challenge

Conformer: Convolution-augmented Transformer for Speech Recognition

https://github.com/MalteHB/-l-ctra

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

https://github.com/ManasRMohanty/DS5500-capstone

KG-BERT: BERT for Knowledge Graph Completion

https://github.com/ManifoldRG/gato-control

A Generalist Agent

https://github.com/MansMeg/IntroML

A Survey of Large Language Models

https://github.com/MarcAntoineAlex/darts

DARTS: Differentiable Architecture Search

https://github.com/Masao-Taketani/AI-Scientist-with-Local-LLMs

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/On_the_Variance_of_the_Adaptive_Learning_Rate_and_Beyond

On the Variance of the Adaptive Learning Rate and Beyond

https://github.com/Maz101/Bert

Semi-supervised Sequence Learning

https://github.com/Maz101/pretrainingdataset

Semi-supervised Sequence Learning

https://github.com/Mees-Molenaar/protein_location

Regularizing and Optimizing LSTM Language Models

https://github.com/MichaelZhouwang/LMlexsub

Semi-supervised Sequence Learning

https://github.com/MichaelisTrofficus/spec_augment

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/Michel-liu/FatFormer

Towards Universal Fake Image Detectors that Generalize Across Generative Models

https://github.com/Milan-Chicago/GLG-Automated-Meta-data-Tagging

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

https://github.com/Mind23-2/MindCode-134

CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

https://github.com/Mind23-2/MindCode-135

Deep contextualized word representations

https://github.com/Mind23-2/MindCode-138

Language Models are Few-Shot Learners

https://github.com/Mind23-2/MindCode-151

XLM-E: Cross-lingual Language Model Pre-training via ELECTRA

https://github.com/Mind23-2/MindCode-156

LXMERT: Learning Cross-Modality Encoder Representations from Transformers

https://github.com/Mind23-2/MindCode-158

Parsing as Pretraining

https://github.com/Mind23-2/MindCode-5/tree/main/ProtoNet

Matching Networks for One Shot Learning

https://github.com/Mind23-2/MindCode-98

Deep contextualized word representations

https://github.com/MindCode-4/code-1/tree/main/visual_bert

VisualBERT: A Simple and Performant Baseline for Vision and Language

https://github.com/MindCode-4/code-12/tree/main/gated-word-character-recurrent-language-model

Gated Word-Character Recurrent Language Model

https://github.com/MindCode-4/code-12/tree/main/isr

ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning

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