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/saprmarks/dictionary_learning

BatchTopK Sparse Autoencoders

https://github.com/saproovarun/Google-Quest-Q-A

How to Fine-Tune BERT for Text Classification?

https://github.com/sarveshsparab/DeepElmoEmbedNer

Deep contextualized word representations

https://github.com/saurabhkulkarni77/BERT_multilabel

Semi-supervised Sequence Learning

https://github.com/saurabhnlp/bert

Semi-supervised Sequence Learning

https://github.com/sayakbanerjee1999/Chat-Bot

End-To-End Memory Networks

https://github.com/sbcblab/Keras-CoDeepNEAT

Evolving Deep Neural Networks

https://github.com/sberbank-ai/ner-bert

Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF

https://github.com/schatty/matching-networks-tf

Matching Networks for One Shot Learning

https://github.com/schenliu/longformer-chinese

Longformer: The Long-Document Transformer

https://github.com/scientific-computing-lab-nrcn/mpi-rigen

MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformers

https://github.com/scientific-computing-lab-nrcn/tokompiler

A Systematic Evaluation of Large Language Models of Code

https://github.com/sciforce/phones-las

Listen, Attend and Spell

https://github.com/sciml/fastdeq.jl

Deep Equilibrium Models

https://github.com/scofield7419/thor-isa

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

https://github.com/scrayish/ML_NLP

Language Models are Few-Shot Learners

https://github.com/scz233/darts

DARTS: Differentiable Architecture Search

https://github.com/sdadas/polish-roberta

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/se4u/cylsh

Sublinear Partition Estimation

https://github.com/seanrjohnson/protein_gibbs_sampler

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

https://github.com/seaweiqing/image2story

A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction

https://github.com/seaweiqing/neuraltalk_plus_charcnn

A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction

https://github.com/sebastianGehrmann/tensorflow-statereader

Recurrent Neural Network Regularization

https://github.com/seharanul17/RNN-LM

Character-Aware Neural Language Models

https://github.com/selmiss/gp-tlstgcn

Language Modeling with Gated Convolutional Networks

https://github.com/semal/bert

Semi-supervised Sequence Learning

https://github.com/semantic-web-company/ptlm_wsid

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

https://github.com/seongho608/ringformer

Conformer: Convolution-augmented Transformer for Speech Recognition

https://github.com/seraphlabs-ca/SentenceMIM-demo

SentenceMIM: A Latent Variable Language Model

https://github.com/seriousssam/deep-image-prior-transfer

DARTS: Differentiable Architecture Search

https://github.com/serp-ai/bark-with-voice-clone

AudioLM: a Language Modeling Approach to Audio Generation

https://github.com/setu4993/convert-labse-tf-pt

Language-agnostic BERT Sentence Embedding

https://github.com/seunghwan1228/ELMO

Deep contextualized word representations

https://github.com/sevvalckc/Turkish-SAD

TurkishBERTweet: Fast and Reliable Large Language Model for Social Media Analysis

https://github.com/sf-18/politicalsynthesis

Neural Abstractive Text Summarization with Sequence-to-Sequence Models

https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning

Sequence-to-Sequence Learning as Beam-Search Optimization

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