Papers with Code 아카이브

Language Modeling

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

https://github.com/kyegomez/Sophia

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

https://github.com/kylrth/procedure-generation

Precise Zero-Shot Dense Retrieval without Relevance Labels

https://github.com/kyutai-labs/hibiki

Moshi: a speech-text foundation model for real-time dialogue

https://github.com/kyutai-labs/moshivis

Moshi: a speech-text foundation model for real-time dialogue

https://github.com/lRomul/argus-freesound

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/lab-emi/cleanumamba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/labmlai/annotated_deep_learning_paper_implementations

Recurrent Highway Networks

https://github.com/labmlai/neox

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

https://github.com/lakahaga/dc-comix-tts

Mixer-TTS: non-autoregressive, fast and compact text-to-speech model conditioned on language model embeddings

https://github.com/lalithjets/surgical_vqa

VisualBERT: A Simple and Performant Baseline for Vision and Language

https://github.com/lambert-x/prolab

Language Models are Few-Shot Learners

https://github.com/langtech-bsc/langtech_tokenizers

Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning

https://github.com/lanwuwei/SPM_toolkit

Character-based Neural Networks for Sentence Pair Modeling

https://github.com/lashoun/hanna-benchmark-asg

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/lastmile-ai/aiconfig

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

https://github.com/lavi-lab/cleva

C$^2$LEVA: Toward Comprehensive and Contamination-Free Language Model Evaluation

https://github.com/layumi/University1652-Baseline

Towards Natural Language-Guided Drones: GeoText-1652 Benchmark with Spatial Relation Matching

https://github.com/lbneon/research

LICHEE: Improving Language Model Pre-training with Multi-grained Tokenization

https://github.com/leanhkhoi/AE_BERT_CROSS_SENTENCES

Adversarial Training for Aspect-Based Sentiment Analysis with BERT

https://github.com/lehoanganh298/BERT-Question-Answering

Semi-supervised Sequence Learning

https://github.com/leihuayi/NetworkEmbedding

DeepWalk: Online Learning of Social Representations

https://github.com/lemon234071/TransformerBaselines

Spelling Error Correction with Soft-Masked BERT

https://github.com/lempiji/golem

AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients

https://github.com/lennijusten/biology-benchmarks

Virology Capabilities Test (VCT): A Multimodal Virology Q&A Benchmark

https://github.com/lennonzurich/lalala

Semi-supervised Sequence Learning

https://github.com/leondz/garak

Assessing Language Model Deployment with Risk Cards

https://github.com/leonguertler/textarena

Evaluating Language Model Agency through Negotiations

https://github.com/leonidasy/fast-vocabulary-transfer

Fast Vocabulary Transfer for Language Model Compression

https://github.com/leonty1/essm

Efficiently Modeling Long Sequences with Structured State Spaces

https://github.com/leopard-ai/betty

DARTS: Differentiable Architecture Search

https://github.com/leowang1217/UCWS

Unsupervised Word Segmentation with Bi-directional Neural Language Model

https://github.com/lersouza/cross-lingual-transfer

On the Cross-lingual Transferability of Monolingual Representations

https://github.com/lesterpjy/numeric-t5

Injecting Numerical Reasoning Skills into Language Models

https://github.com/lezhang7/msa-augmentor

Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation

https://github.com/lhao499/llm_large_context

Blockwise Parallel Transformer for Large Context Models

https://github.com/liamcli/darts

DARTS: Differentiable Architecture Search

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