2024
Enhancing Large Language Models through Adaptive Tokenizers
NeurIPS 2024poster
Tokenizers serve as crucial interfaces between models and linguistic data, substantially influencing the efficacy and precision of large language models (LLMs). Traditional tokenization methods often rely on static frequency-based statistics and are not inherently synchronized with LLM architectures…