Papers with Code 아카이브

Language Modeling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/Yunodo/maxup

MaxUp: A Simple Way to Improve Generalization of Neural Network Training

https://github.com/YunwenTechnology/Unilm

Unified Language Model Pre-training for Natural Language Understanding and Generation

https://github.com/YushiChen/Auto-CNN-HSI-Classification

DARTS: Differentiable Architecture Search

https://github.com/YuweiYin/HLT-MT

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/ZIZUN/MAFiD

Mega: Moving Average Equipped Gated Attention

https://github.com/Zefty/rag-end2end-retriever

REALM: Retrieval-Augmented Language Model Pre-Training

https://github.com/Zehui127/SQUAD_BERT

Semi-supervised Sequence Learning

https://github.com/Zeng-WH/PrefixTuning-Fix

Prefix-Tuning: Optimizing Continuous Prompts for Generation

https://github.com/ZhengkunTian/OpenTransformer

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/Zhiyu-Chen/SIGIR2020-BERT-Table-Search

Table Search Using a Deep Contextualized Language Model

https://github.com/Ziyang412/VideoTree

VideoAgent: Long-form Video Understanding with Large Language Model as Agent

https://github.com/ZubinGou/rho

Rho-1: Not All Tokens Are What You Need

https://github.com/a-rios/ats-models

Longformer: The Long-Document Transformer

https://github.com/a-taniguchi/SpCoSLAM

Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping

https://github.com/a-taniguchi/SpCoSLAM2

Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping

https://github.com/a-taniguchi/SpCoSLAM_evaluation

Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping

https://github.com/a414351664/Bert_MRC

Semi-supervised Sequence Learning

https://github.com/aadil-srivastava01/End-To-End-Memory-Networks

End-To-End Memory Networks

https://github.com/aaronbae/ModifiedSentenceVAE

Generating Sentences from a Continuous Space

https://github.com/abacusai/long-context

A Length-Extrapolatable Transformer

https://github.com/abcSup/captionamerica

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

https://github.com/abcp4/DAPytorch

Neural Architecture Search with Reinforcement Learning

https://github.com/abcp4/MyDarts

DARTS: Differentiable Architecture Search

https://github.com/abdumaa/hiqualprop

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/abhaskumarsinha/Corpus2GPT

Language Models are Few-Shot Learners

https://github.com/abhaskumarsinha/MinimalGPT

Language Models are Few-Shot Learners

https://github.com/abhiagg92/bert_sentiment

Semi-supervised Sequence Learning

https://github.com/abhishekanand1710/noiseandbias

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/abril4416/kgen_vqa

Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection

https://github.com/acca3003/d2l-es

ControlVAE: Tuning, Analytical Properties, and Performance Analysis

https://github.com/accessai/dynamic_word_embeddings

Dynamic Word Embeddings

https://github.com/adamkarvonen/sae_kl_finetune

Low-Rank Adapting Models for Sparse Autoencoders

https://github.com/adammenges/DARTS-PyTorch

DARTS: Differentiable Architecture Search

https://github.com/adamx97/Data-Science-Advanced-Capstone

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

https://github.com/adieyal/sd-dynamic-prompts

Optimizing Prompts for Text-to-Image Generation

https://github.com/adlik/vllm

Efficient Memory Management for Large Language Model Serving with PagedAttention

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