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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/areffarhadi/mamba-asr

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/ari-holtzman/genlm

Improving Neural Language Models with a Continuous Cache

https://github.com/arjundussa65/Thesis-2020

Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models

https://github.com/ars-ashuha/variational-dropout-sparsifies-dnn

Bayesian Sparsification of Recurrent Neural Networks

https://github.com/arshadshk/GatedWord-Character_Recurrent_Language_Model

Gated Word-Character Recurrent Language Model

https://github.com/artetxem/phrase2vec

Unsupervised Statistical Machine Translation

https://github.com/arunppsg/set2set

Order Matters: Sequence to sequence for sets

https://github.com/arvieFrydenlund/awd-lstm-lm

Improving Neural Language Models with a Continuous Cache

https://github.com/arvind385801/paraphrasegen

Generating Sentences from a Continuous Space

https://github.com/arvindrajan92/DTrOCR

DTrOCR: Decoder-only Transformer for Optical Character Recognition

https://github.com/asahi417/lmppl

Language Models are Few-Shot Learners

https://github.com/ashwanitanwar/nmt-transfer-learning-xlm-r

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/asif-hanif/baple

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

https://github.com/askaydevs/distillbert-qa

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

https://github.com/astanway/gated-conv-nets

Language Modeling with Gated Convolutional Networks

https://github.com/asyml/texar/tree/master/examples/text_style_transfer

Unsupervised Text Style Transfer using Language Models as Discriminators

https://github.com/atharva20038/music4all

Simple and Controllable Music Generation

https://github.com/audio-westlakeu/rct

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/augustepoiroux/LeanInteract

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

https://github.com/augustgw/early-exit-transformer

Conformer: Convolution-augmented Transformer for Speech Recognition

https://github.com/aunabil4602/bnlp-workshop-task2-2023

BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla

https://github.com/autobotasia/vibert

Semi-supervised Sequence Learning

https://github.com/autonlab/KeyClass

Text Classification Using Label Names Only: A Language Model Self-Training Approach

https://github.com/avramandrei/BERT-Sequence-Labeling

UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition Extraction

https://github.com/avramandrei/UPB-at-SemEval-2020-Task-6-Pretrained-Language-Models-for-DefinitionExtraction

UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition Extraction

https://github.com/awni00/abstract_transformer

Disentangling and Integrating Relational and Sensory Information in Transformer Architectures

https://github.com/awslabs/autogluon

Multi-objective Asynchronous Successive Halving

https://github.com/awslabs/gap-text2sql

Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

https://github.com/axiomlab/Cable

Pointer Sentinel Mixture Models

https://github.com/axrwl/gateloop

GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

https://github.com/ayeffkay/rubert-tiny

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

https://github.com/baai-dcai/segvol

M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

https://github.com/baai-zlab/coig

Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

https://github.com/baaivision/eva

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

https://github.com/babelscape/alert

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

https://github.com/baidu-research/warp-ctc

First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs

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