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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/mingdali6717/ensemble-of-retrievers

Generate rather than Retrieve: Large Language Models are Strong Context Generators

https://github.com/mingyue-cheng/convtimenet

Advancing Time Series Classification with Multimodal Language Modeling

https://github.com/mingyue-cheng/formertime

Advancing Time Series Classification with Multimodal Language Modeling

https://github.com/mingyue-cheng/timemae

Advancing Time Series Classification with Multimodal Language Modeling

https://github.com/minhtriet/gridworld

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

https://github.com/miroblog/AdaptiveAttention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/mithunpaul08/bert_tensorflow

Semi-supervised Sequence Learning

https://github.com/mitvis/vistext

Unifying Vision-and-Language Tasks via Text Generation

https://github.com/miyamankyushu/DCGAN

On the Variance of the Adaptive Learning Rate and Beyond

https://github.com/mkavim/finetune_bert

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

https://github.com/mkfilipiuk/VAE-CF

Variational Autoencoders for Collaborative Filtering

https://github.com/mkshing/DiffFit-pytorch

BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models

https://github.com/ml-jku/l2m

Decision Transformer: Reinforcement Learning via Sequence Modeling

https://github.com/mlcommons/submissions_algorithms

Scalable Second Order Optimization for Deep Learning

https://github.com/mlfoundations/open_clip

Data Filtering Networks

https://github.com/mlfoundations/open_flamingo

Flamingo: a Visual Language Model for Few-Shot Learning

https://github.com/mlvc-lab/Classification-NAS

DARTS: Differentiable Architecture Search

https://github.com/mnikitin/RAdam

On the Variance of the Adaptive Learning Rate and Beyond

https://github.com/mnm-rnd/elsa-voice-asr

Listen, Attend and Spell

https://github.com/mobile-sensing-and-ubicomp-laboratory/normwear

Chronos: Learning the Language of Time Series

https://github.com/modelscope/modelscope

OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

https://github.com/modeltc/lightllm

FastSwitch: Optimizing Context Switching Efficiency in Fairness-aware Large Language Model Serving

https://github.com/moein-shariatnia/Pix2Seq

Pix2seq: A Language Modeling Framework for Object Detection

https://github.com/mojesty/professor_forcing

Professor Forcing: A New Algorithm for Training Recurrent Networks

https://github.com/mojivalipour/symbolicgpt

SymbolicGPT: A Generative Transformer Model for Symbolic Regression

https://github.com/monologg/R-BERT

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

https://github.com/monologg/distilkobert

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

https://github.com/montallen/qrnn-rna-localization

Quasi-Recurrent Neural Networks

https://github.com/moon23k/Transformer_Archs

Universal Transformers

https://github.com/mozilla/DeepSpeech

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/mpc001/Visual_Speech_Recognition_for_Multiple_Languages

End-to-end Audio-visual Speech Recognition with Conformers

https://github.com/mpc001/auto_avsr

End-to-end Audio-visual Speech Recognition with Conformers

https://github.com/mrdbourke/tensorflow-deep-learning

Universal Language Model Fine-tuning for Text Classification

https://github.com/mrityunjayojha10/Image-Caption-Generation

Where to put the Image in an Image Caption Generator

https://github.com/mrjleo/ranking-models

Passage Re-ranking with BERT

https://github.com/mrlab-ai/NL2Plan

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

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