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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/wenet-e2e/west

The Llama 3 Herd of Models

https://github.com/wenet-e2e/wetts

Unified Mandarin TTS Front-end Based on Distilled BERT Model

https://github.com/whisperspeech/whisperspeech

Simple and Controllable Music Generation

https://github.com/whull/ONLSTM

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

https://github.com/why2000/DuReader-bert

Semi-supervised Sequence Learning

https://github.com/wi-pi/GDPR

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

https://github.com/williamleif/GraphSAGE

DeepWalk: Online Learning of Social Representations

https://github.com/willxxy/ecg-bench

ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling

https://github.com/wiseodd/controlled-text-generation

Generating Sentences from a Continuous Space

https://github.com/woailaosang/repo_treasure

Conditional BERT Contextual Augmentation

https://github.com/woozzu/dong_iccv_2017

Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

https://github.com/worksapplications/uzushio

Deduplicating Training Data Makes Language Models Better

https://github.com/wqliu657/UniVL

UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation

https://github.com/wujsAct/DeepLearningModels

End-To-End Memory Networks

https://github.com/wutaiqiang/shadow-ft

LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language Models

https://github.com/wuyenlin/federated-learning

Learning Private Neural Language Modeling with Attentive Aggregation

https://github.com/wxh1996/VideoAgent

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

https://github.com/wxt1997/Transformer-Transducer

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

https://github.com/wzh326/R-Drop

R-Drop: Regularized Dropout for Neural Networks

https://github.com/wzzzd/LM_NER

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/x-lance/neusym-rag

Language Models are Few-Shot Learners

https://github.com/xavierpuigf/virtualhome

Pre-Trained Language Models for Interactive Decision-Making

https://github.com/xesdiny/test-bert-master

Semi-supervised Sequence Learning

https://github.com/xhan77/AdaptaBERT

Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling

https://github.com/xi-j/mamba-asr

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/xiaomin418/cfsum

UNITER: UNiversal Image-TExt Representation Learning

https://github.com/xiaopingzhong/bert-finetune-for-classfier

Semi-supervised Sequence Learning

https://github.com/xiaopp123/bert_explain

Semi-supervised Sequence Learning

https://github.com/xiaoqian19940510/text-classification-

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/xiaoqian19940510/text-classification-surveys

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/xinding-sys/StreamMind

Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

https://github.com/xinykou/Against_Jailbreak

A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model

https://github.com/xitianxiaofeixue/BERT

Semi-supervised Sequence Learning

https://github.com/xqx12/daily-info

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

https://github.com/xuduo35/InstructPix2Pix

InstructPix2Pix: Learning to Follow Image Editing Instructions

https://github.com/xusenlinzy/api-for-open-llm

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

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