3 papers
cs.CL2025
Beyond Text Compression: Evaluating Tokenizers Across Scales
Jonas F. Lotz, António V. Lopes, Stephan Peitz +2
The choice of tokenizer can profoundly impact language model performance, yet accessible and reliable evaluations of tokenizer quality remain an open challenge. Inspired by scaling…
cs.CL2025
Multilingual Pretraining for Pixel Language Models
Ilker Kesen, Jonas F. Lotz, Ingo Ziegler +2
Pixel language models operate directly on images of rendered text, eliminating the need for a fixed vocabulary. While these models have demonstrated strong capabilities for downstr…
cs.CL2025
Overcoming Vocabulary Constraints with Pixel-level Fallback
Jonas F. Lotz, Hendra Setiawan, Stephan Peitz +1
Subword tokenization requires balancing computational efficiency and vocabulary coverage, which often leads to suboptimal performance on languages and scripts not prioritized durin…