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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/xuzhezhaozhao/bert_reading

Semi-supervised Sequence Learning

https://github.com/xvyaward/qeft

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

https://github.com/xycforgithub/MultiTask-MRC

Multi-Task Deep Neural Networks for Natural Language Understanding

https://github.com/xzf-thu/audio-reasoner

Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models

https://github.com/yan-gao-GY/FedScale

FedScale: Benchmarking Model and System Performance of Federated Learning at Scale

https://github.com/yang-ze-kang/PassageReranking

Passage Re-ranking with BERT

https://github.com/yang3121099/LLM-Neo

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

https://github.com/yanghaha0908/fasthubert

Pushing the Limits of Unsupervised Unit Discovery for SSL Speech Representation

https://github.com/yangheng95/LC-ABSA

Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification

https://github.com/yangjianxin1/longqlora

Extending Context Window of Large Language Models via Positional Interpolation

https://github.com/yangletliu/finlora

BloombergGPT: A Large Language Model for Finance

https://github.com/yangling0818/buffer-of-thought-llm

ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates

https://github.com/yangling0818/supercorrect-llm

ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates

https://github.com/yangrui123/Hidden

Pointer Sentinel Mixture Models

https://github.com/yangrui525/kg-rank

ExpertQA: Expert-Curated Questions and Attributed Answers

https://github.com/yangxueruivs/DFSMN

Deep-FSMN for Large Vocabulary Continuous Speech Recognition

https://github.com/yangyijune/mma-diffusion

GuardT2I: Defending Text-to-Image Models from Adversarial Prompts

https://github.com/yangyucheng000/Paper-3/tree/main/dir-mindspore-main

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

https://github.com/yangyucheng000/University/tree/main/model-1/olmo

OLMo: Accelerating the Science of Language Models

https://github.com/yangyucheng000/University/tree/main/model-1/openelm

OpenELM: An Efficient Language Model Family with Open Training and Inference Framework

https://github.com/yangyucheng000/University/tree/main/model-1/pix2struct

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding

https://github.com/yangyucheng000/University/tree/main/model-1/roc_bert

COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search

https://github.com/yangyucheng000/University/tree/main/model-2/blip_2

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

https://github.com/yangyucheng000/University/tree/main/model-2/electra

ELECTRAMed: a new pre-trained language representation model for biomedical NLP

https://github.com/yangyucheng000/University/tree/main/model-2/gpt_neox

GPT-NeoX-20B: An Open-Source Autoregressive Language Model

https://github.com/yangyucheng000/University/tree/main/model-2/gpt_neox_japanese

GPT-NeoX-20B: An Open-Source Autoregressive Language Model

https://github.com/yangyucheng000/University/tree/main/model-2/internlm

InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD

https://github.com/yangyucheng000/University/tree/main/model-3/roberta

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/yangyucheng000/University/tree/main/model-3/stablelm

Stable LM 2 1.6B Technical Report

https://github.com/yangzhengyi98/dreamrec

Large Language Model Can Interpret Latent Space of Sequential Recommender

https://github.com/yangzonglin1994/bilm-tf-extended

Deep contextualized word representations

https://github.com/yao0510/NLP-2020-EmotionGIF

EmotionGIF-Yankee: A Sentiment Classifier with Robust Model Based Ensemble Methods

https://github.com/yaof20/real

Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization

https://github.com/yaoli/arctic-capgen-vid

Oracle performance for visual captioning

https://github.com/yfreedomliTHU/mos-pytorch1.1

Breaking the Softmax Bottleneck: A High-Rank RNN Language Model

https://github.com/yhzhu99/medagentboard

ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

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