Papers with Code 아카이브

Language Modeling

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코드

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

https://github.com/localminimum/qanet

Character-Aware Neural Language Models

https://github.com/locuslab/impsq

Deep Equilibrium Models

https://github.com/locuslab/monotone_op_net

Deep Equilibrium Models

https://github.com/logpai/logparser

Self-Supervised Log Parsing

https://github.com/longbai1006/surgical-vqla

VisualBERT: A Simple and Performant Baseline for Vision and Language

https://github.com/longbowking/bert

Semi-supervised Sequence Learning

https://github.com/longshaocong/dgmamba

VMamba: Visual State Space Model

https://github.com/lorylei/DARTS-et

DARTS: Differentiable Architecture Search

https://github.com/lostoxygen/llm-confidentiality

Prefix-Tuning: Optimizing Continuous Prompts for Generation

https://github.com/lovecambi/qebrain

"Bilingual Expert" Can Find Translation Errors

https://github.com/lovedavidsilva/bert_old_version

Semi-supervised Sequence Learning

https://github.com/lsl001006/zone

InstructPix2Pix: Learning to Follow Image Editing Instructions

https://github.com/lsqdecodebox/NLP-Comptition-review

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/ltruncel/Microsoft_Azure_50daysofudacity

Language Models are Few-Shot Learners

https://github.com/lucashueda/long_sentence_transformer

Longformer: The Long-Document Transformer

https://github.com/lucidrains/CoCa-pytorch

PaLM: Scaling Language Modeling with Pathways

https://github.com/lucidrains/FLASH-pytorch

Primer: Searching for Efficient Transformers for Language Modeling

https://github.com/lucidrains/PaLM-jax

PaLM: Scaling Language Modeling with Pathways

https://github.com/lucidrains/PaLM-pytorch

PaLM: Scaling Language Modeling with Pathways

https://github.com/lucidrains/audiolm-pytorch

AudioLM: a Language Modeling Approach to Audio Generation

https://github.com/lucidrains/block-recurrent-transformer-pytorch

Block-Recurrent Transformers

https://github.com/lucidrains/coco-lm-pytorch

COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

https://github.com/lucidrains/compressive-transformer-pytorch

Stabilizing Transformers for Reinforcement Learning

https://github.com/lucidrains/conformer

Conformer: Convolution-augmented Transformer for Speech Recognition

https://github.com/lucidrains/electra-pytorch

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

https://github.com/lucidrains/ema-pytorch

Switch EMA: A Free Lunch for Better Flatness and Sharpness

https://github.com/lucidrains/feedback-transformer-pytorch

Addressing Some Limitations of Transformers with Feedback Memory

https://github.com/lucidrains/flamingo-pytorch

Flamingo: a Visual Language Model for Few-Shot Learning

https://github.com/lucidrains/gated-state-spaces-pytorch

Long Range Language Modeling via Gated State Spaces

https://github.com/lucidrains/hourglass-transformer-pytorch

Hierarchical Transformers Are More Efficient Language Models

https://github.com/lucidrains/infini-transformer-pytorch

Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

https://github.com/lucidrains/lion-pytorch

Symbolic Discovery of Optimization Algorithms

https://github.com/lucidrains/local-attention

Efficient Content-Based Sparse Attention with Routing Transformers

https://github.com/lucidrains/long-short-transformer

Long-Short Transformer: Efficient Transformers for Language and Vision

https://github.com/lucidrains/magvit2-pytorch

Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

https://github.com/lucidrains/marge-pytorch

Pre-training via Paraphrasing

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