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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/dortsur/heavywater_simplexwater

Robust Distortion-free Watermarks for Language Models

https://github.com/dpalominop/ULMFit

Universal Language Model Fine-tuning for Text Classification

https://github.com/dpfried/rnng-bert

Recurrent Neural Network Grammars

https://github.com/dqqcasia/st

Pay Less Attention with Lightweight and Dynamic Convolutions

https://github.com/dragen1860/DARTS-PyTorch

DARTS: Differentiable Architecture Search

https://github.com/duanchi1230/NLP_Project_AI2_Reasoning_Challenge

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/duxiaoman-di/xuanyuan

Self-QA: Unsupervised Knowledge Guided Language Model Alignment

https://github.com/duyunshu/bert-sentiment-analysis

Semi-supervised Sequence Learning

https://github.com/dynamite321/codeguardplus

Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions

https://github.com/dzqjorking/transpose

Semi-supervised Sequence Learning

https://github.com/ebouteillon/freesound-audio-tagging-2019

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/ecnu-cross-innovation-lab/ent

Factorized Neural Transducer for Efficient Language Model Adaptation

https://github.com/ecnu-icalk/educhat

EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education

https://github.com/ed-fish/Geo-Sign

Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language Translation

https://github.com/eecrazy/TransBERT_ijcai2019

Story Ending Prediction by Transferable BERT

https://github.com/efficient-large-model/vila

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

https://github.com/elanmart/psmm

Pointer Sentinel Mixture Models

https://github.com/elaynelemos/gector-api

LM-Critic: Language Models for Unsupervised Grammatical Error Correction

https://github.com/elgazzarr/fmri-s4

Efficiently Modeling Long Sequences with Structured State Spaces

https://github.com/eliavmor-tau/DoLMUnderstandFrequentWordsBetter

oLMpics -- On what Language Model Pre-training Captures

https://github.com/eml-eda/plinio

DARTS: Differentiable Architecture Search

https://github.com/emorynlp/friendsqa

Transformers to Learn Hierarchical Contexts in Multiparty Dialogue for Span-based Question Answering

https://github.com/emrekuecuek/COMP541

Memory-Efficient Adaptive Optimization

https://github.com/enealor/pytorch-sm3

Memory-Efficient Adaptive Optimization

https://github.com/enhuiz/vall-e

Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

https://github.com/enzomuschik/distilfnd

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

https://github.com/epfml/collaborative-attention

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

https://github.com/eric-erki/wav2letter

Letter-Based Speech Recognition with Gated ConvNets

https://github.com/eric-mitchell/direct-preference-optimization

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

https://github.com/eric-mitchell/serac

Memory-Based Model Editing at Scale

https://github.com/ericlbuehler/mistral.rs

Fast Inference from Transformers via Speculative Decoding

https://github.com/ericperfect/Bert_Position_BiLSTM_Attention_CRF_LSTMDecoder

Semi-supervised Sequence Learning

https://github.com/erika-n/GPTzip

LLMZip: Lossless Text Compression using Large Language Models

https://github.com/erolm-a/colla-framework

Entities as Experts: Sparse Memory Access with Entity Supervision

https://github.com/eternityyw/tram-benchmark

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/eth-sri/sven

CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

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