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Tokenization is more than compression
CW Schmidt, V Reddy, H Zhang, A Alameddine… - ar** llm-driven testsuite for compiler validation
Large language models (LLMs) are a new and powerful tool for a wide span of applications
involving natural language and demonstrate impressive code generation abilities. The goal …
involving natural language and demonstrate impressive code generation abilities. The goal …
An Analysis of Tokenization: Transformers under Markov Data
While there has been a large body of research attempting to circumvent tokenization for
language modeling (Clark et al. 2022, Xue et al. 2022), the current consensus is that it is a …
language modeling (Clark et al. 2022, Xue et al. 2022), the current consensus is that it is a …
Deep Learning and Machine Learning--Natural Language Processing: From Theory to Application
With a focus on natural language processing (NLP) and the role of large language models
(LLMs), we explore the intersection of machine learning, deep learning, and artificial …
(LLMs), we explore the intersection of machine learning, deep learning, and artificial …
The foundations of tokenization: Statistical and computational concerns
Tokenization-the practice of converting strings of characters from an alphabet into
sequences of tokens over a vocabulary-is a critical step in the NLP pipeline. The use of …
sequences of tokens over a vocabulary-is a critical step in the NLP pipeline. The use of …
Towards objective and unbiased decision assessments with llm-enhanced hierarchical attention networks
How objective and unbiased are we while making decisions? This work investigates
cognitive bias identification in high-stake decision making process by human experts …
cognitive bias identification in high-stake decision making process by human experts …
Theoretical Analysis of Byte-Pair Encoding
Byte-Pair Encoding (BPE) is a widely used method for subword tokenization, with origins in
grammar-based text compression. It is employed in a variety of language processing tasks …
grammar-based text compression. It is employed in a variety of language processing tasks …