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Collections including paper arxiv:2105.13626

Papers - Training - Text - Vocabulary - SentencePiece

ByT5: Towards a token-free future with pre-trained byte-to-byte models

Paper • 2105.13626 • Published May 28, 2021 • 3

Papers - Encoders - Bytes - More Depth than Decoder

ByT5: Towards a token-free future with pre-trained byte-to-byte models

Paper • 2105.13626 • Published May 28, 2021 • 3
Byte Latent Transformer: Patches Scale Better Than Tokens

Paper • 2412.09871 • Published Dec 13, 2024 • 88

Papers - Training - Token Free - Bytes or Characters

ByT5: Towards a token-free future with pre-trained byte-to-byte models

Paper • 2105.13626 • Published May 28, 2021 • 3
CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation

Paper • 2103.06874 • Published Mar 11, 2021 • 1

Papers - Training - Bytes - No Tokenizer

ByT5: Towards a token-free future with pre-trained byte-to-byte models

Paper • 2105.13626 • Published May 28, 2021 • 3
Byte Latent Transformer: Patches Scale Better Than Tokens

Paper • 2412.09871 • Published Dec 13, 2024 • 88
MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

Paper • 2410.20771 • Published Oct 28, 2024 • 3

Papers - Multilingual - Benchmarks

HyperCLOVA X Technical Report

Paper • 2404.01954 • Published Apr 2, 2024 • 20
ByT5: Towards a token-free future with pre-trained byte-to-byte models

Paper • 2105.13626 • Published May 28, 2021 • 3
Byte Latent Transformer: Patches Scale Better Than Tokens

Paper • 2412.09871 • Published Dec 13, 2024 • 88

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping

Paper • 2402.14083 • Published Feb 21, 2024 • 47
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Paper • 2305.13245 • Published May 22, 2023 • 5
Training a T5 Using Lab-sized Resources

Paper • 2208.12097 • Published Aug 25, 2022 • 1
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints

Paper • 2212.05055 • Published Dec 9, 2022 • 5

Papers - Training - Synthetic Noise

CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Paper • 2002.08155 • Published Feb 19, 2020 • 2
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise

Paper • 2212.11685 • Published Dec 22, 2022 • 2
ReNoise: Real Image Inversion Through Iterative Noising

Paper • 2403.14602 • Published Mar 21, 2024 • 19
ByT5: Towards a token-free future with pre-trained byte-to-byte models

Paper • 2105.13626 • Published May 28, 2021 • 3

Papers - Multilingual

A Biomedical Entity Extraction Pipeline for Oncology Health Records in Portuguese

Paper • 2304.08999 • Published Apr 18, 2023 • 2
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

Paper • 2309.09400 • Published Sep 17, 2023 • 84
Robust Open-Vocabulary Translation from Visual Text Representations

Paper • 2104.08211 • Published Apr 16, 2021 • 1
Poro 34B and the Blessing of Multilinguality

Paper • 2404.01856 • Published Apr 2, 2024 • 13

Papers - Training

SELF: Language-Driven Self-Evolution for Large Language Model

Paper • 2310.00533 • Published Oct 1, 2023 • 2
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length

Paper • 2310.00576 • Published Oct 1, 2023 • 2
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity

Paper • 2305.13169 • Published May 22, 2023 • 3
Transformers Can Achieve Length Generalization But Not Robustly

Paper • 2402.09371 • Published Feb 14, 2024 • 13

Papers - Text - Encoders

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 16
Transformers Can Achieve Length Generalization But Not Robustly

Paper • 2402.09371 • Published Feb 14, 2024 • 13
Triple-Encoders: Representations That Fire Together, Wire Together

Paper • 2402.12332 • Published Feb 19, 2024 • 2
BERTs are Generative In-Context Learners

Paper • 2406.04823 • Published Jun 7, 2024 • 1

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