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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/neburseni/NLP

Universal Language Model Fine-tuning for Text Classification

https://github.com/necla-ml/SNLI-VE

UNITER: UNiversal Image-TExt Representation Learning

https://github.com/neelsjain/baseline-defenses

Detecting Language Model Attacks with Perplexity

https://github.com/nehalelkaref/towards-a-better-isotropy-to-detect-hatespeech

Representation Degeneration Problem in Training Natural Language Generation Models

https://github.com/neil-zeng/asr

Listen, Attend and Spell

https://github.com/neuir/llm-qe

Repetition Improves Language Model Embeddings

https://github.com/neuralmagic/lm-evaluation-harness

Language Models are Few-Shot Learners

https://github.com/neuspell/neuspell

One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling

https://github.com/neutralzz/billa

The Pile: An 800GB Dataset of Diverse Text for Language Modeling

https://github.com/neverix/rlhf-trojan-2024-cod

Towards Efficient Exact Optimization of Language Model Alignment

https://github.com/newRevelation/DL

Conditional BERT Contextual Augmentation

https://github.com/nextbigwhat-ai/sentiment-analysis-pytorch

Universal Language Model Fine-tuning for Text Classification

https://github.com/nguyentthong/temporal_recipe

Temporal-Oriented Recipe for Transferring Large Vision-Language Model to Video Understanding

https://github.com/nicholasbao/nlp_job

Semi-supervised Sequence Learning

https://github.com/nico-koltermann/contextual-evolution-of-heuristics

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

https://github.com/nicolafan/image-captioning-cnn-rnn

Where to put the Image in an Image Caption Generator

https://github.com/nicolaszucchet/minimal-lru

Efficiently Modeling Long Sequences with Structured State Spaces

https://github.com/nikdnaik/accelerating_nas-1

Accelerating Neural Architecture Search using Performance Prediction

https://github.com/nikhilbarhate99/min-decision-transformer

Decision Transformer: Reinforcement Learning via Sequence Modeling

https://github.com/nikhilrathaur/Handwriting-to-Digital-Text

Character-Level Incremental Speech Recognition with Recurrent Neural Networks

https://github.com/nikita270a/BayesianDARTS

DARTS: Differentiable Architecture Search

https://github.com/ninghaohello/Polysemous-Network-Embedding

Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

https://github.com/ninglab/ecellm

Mistral 7B

https://github.com/ningyuxu/tip_of_tongue

OLMo: Accelerating the Science of Language Models

https://github.com/ninoxjy/graph-embedding

DeepWalk: Online Learning of Social Representations

https://github.com/nishee0521/Sarcasm-Detector

Universal Language Model Fine-tuning for Text Classification

https://github.com/nithinksath96/Speech_Recognition

Listen, Attend and Spell

https://github.com/niyunsheng/ems-sd

Prefix-Tuning: Optimizing Continuous Prompts for Generation

https://github.com/njunlp/mcsd

SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification

https://github.com/njunlp/mmt-llm

OpenICL: An Open-Source Framework for In-context Learning

https://github.com/nkcr/overlap-ml

Regularizing and Optimizing LSTM Language Models

https://github.com/nku-hlt/promptrank

PromptRank: Unsupervised Keyphrase Extraction Using Prompt

https://github.com/nlp-research/bilm-tf

Deep contextualized word representations

https://github.com/nlpodyssey/rwkv.f90

Accelerating Large Language Model Decoding with Speculative Sampling

https://github.com/nlpodyssey/verbaflow

The Pile: An 800GB Dataset of Diverse Text for Language Modeling

https://github.com/nlx-group/overlapy

Language Models are Few-Shot Learners

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