{"total":18,"rows":[{"id":"2105.13626","title":"ByT5: Towards a token-free future with pre-trained byte-to-byte models","created":"2021-05-28","cited_by_count":509,"area":null},{"id":"2307.10169","title":"Challenges and Applications of Large Language Models","created":"2023-07-19","cited_by_count":254,"area":null},{"id":"2103.06874","title":"CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation","created":"2021-03-11","cited_by_count":232,"area":null},{"id":"2305.15425","title":"Language Model Tokenizers Introduce Unfairness Between Languages","created":"2023-05-17","cited_by_count":214,"area":null},{"id":"2412.09871","title":"Byte Latent Transformer: Patches Scale Better Than Tokens","created":"2024-12-13","cited_by_count":146,"area":null},{"id":"2112.10508","title":"Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP","created":"2021-12-20","cited_by_count":132,"area":null},{"id":"2109.02550","title":"You should evaluate your language model on marginal likelihood over tokenisations","created":"2021-09-06","cited_by_count":30,"area":null},{"id":"2502.01637","title":"Scaling Embedding Layers in Language Models","created":"2025-02-03","cited_by_count":20,"area":null},{"id":"2404.03626","title":"Training LLMs over Neurally Compressed Text","created":"2024-04-04","cited_by_count":17,"area":null},{"id":"2510.21909","title":"Explaining and Mitigating Crosslingual Tokenizer Inequities","created":"2025-10-24","cited_by_count":7,"area":null},{"id":"2511.21622","title":"On the Origin of Algorithmic Progress in AI","created":"2025-11-26","cited_by_count":6,"area":null},{"id":"2403.11130","title":"Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models","created":"2024-03-17","cited_by_count":5,"area":null},{"id":"2305.14571","title":"From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding","created":"2023-05-23","cited_by_count":4,"area":null},{"id":"2602.04289","title":"Proxy Compression for Language Modeling","created":"2026-02-04","cited_by_count":3,"area":null},{"id":"2310.17284","title":"Learning to Abstract with Nonparametric Variational Information Bottleneck","created":"2023-10-26","cited_by_count":2,"area":null},{"id":"2604.16656","title":"Defragmenting Language Models: An Interpretability-based Approach for Vocabulary Expansion","created":"2026-04-17","cited_by_count":2,"area":null},{"id":"2303.14588","title":"Fine-Tashkeel: Finetuning Byte-Level Models for Accurate Arabic Text Diacritization","created":"2023-03-25","cited_by_count":1,"area":null},{"id":"2210.03251","title":"Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints","created":"2022-10-06","cited_by_count":0,"area":null}],"next_cursor":null}