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Language Modeling

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/MindSpore-scientific-2/code-14/tree/main/layoutlmv3

LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking

https://github.com/MindSpore-scientific-2/code-3/tree/main/TSGD

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/MindSpore-scientific-2/code-4/tree/main/Hyena-A-Convolutional-Neural-Network-for-Modelling-Sentences

Hyena Hierarchy: Towards Larger Convolutional Language Models

https://github.com/MindSpore-scientific-2/code-5/tree/main/Deep-Gradient-Compression

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

https://github.com/MindSpore-scientific-2/code-5/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific-2/code-8/tree/main/shallow-rnns

Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text Normalization

https://github.com/MindSpore-scientific-2/code-8/tree/main/text-to-music

LP-MusicCaps: LLM-Based Pseudo Music Captioning

https://github.com/MindSpore-scientific-2/code-9/tree/main/Deep-Gradient-Compression

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

https://github.com/MindSpore-scientific-2/code-9/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-1/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-1/tree/main/shallow-rnns

Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text Normalization

https://github.com/MindSpore-scientific/code-10/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-10/tree/main/ShortFuse-Biomedical-Time-Series

FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams

https://github.com/MindSpore-scientific/code-11/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-12/tree/main/Block_Model

Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models

https://github.com/MindSpore-scientific/code-12/tree/main/Deep-Gradient-Compression

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

https://github.com/MindSpore-scientific/code-12/tree/main/INR-Implicit-Neural-Representations-with-Periodic-Activation-Functions

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/MindSpore-scientific/code-13/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-13/tree/main/QuantExplainNLP_AlgoAnalysis

NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark

https://github.com/MindSpore-scientific/code-13/tree/main/ShortFuse-Biomedical-Time-Series

FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams

https://github.com/MindSpore-scientific/code-14/tree/main/ReSeg

Recurrent Neural Network Regularization

https://github.com/MindSpore-scientific/code-14/tree/main/TSGD

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/MindSpore-scientific/code-2/tree/main/stochastic-attention-head-removal-a-simple

Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training

https://github.com/MindSpore-scientific/code-4/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-5/tree/main/ReSeg

Recurrent Neural Network Regularization

https://github.com/MindSpore-scientific/code-7/tree/main/LayoutLMv2

LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding

https://github.com/MindSpore-scientific/code-8/tree/main/Knowing-When-to-Look-Adaptive-Attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/MindSpore-scientific/code-8/tree/main/QuantExplainNLP_AlgoAnalysis

The Curious Case of Neural Text Degeneration

https://github.com/MirunaPislar/multi-head-attention-labeller

Semi-supervised Multitask Learning for Sequence Labeling

https://github.com/Misoknisky/Bert-MultiGpu

Semi-supervised Sequence Learning

https://github.com/MiuGod0126/ConvS2S_Paddle

Cross-lingual Language Model Pretraining

https://github.com/Monireh2/kg-deductive-reasoner

End-To-End Memory Networks

https://github.com/MostafaDehghani/bAbI-T2T

Universal Transformers

https://github.com/MrMao/wav2letter

Letter-Based Speech Recognition with Gated ConvNets

https://github.com/MsAmberWelch/Privacy-Engineering

Federated Learning for Mobile Keyboard Prediction

https://github.com/Muhammad-Huzaifaa/ObjectCompose

LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images

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