collaborators

5 papers

cs.CL2025

On Finding Inconsistencies in Documents

Charles J. Lovering, Seth Ebner, Brandon Smock +5

Professionals in academia, law, and finance audit their documents because inconsistencies can result in monetary, reputational, and scientific costs. Language models (LMs) have the…

cs.CL2025

Entropy-Driven Pre-Tokenization for Byte-Pair Encoding

Yifan Hu, Frank Liang, Dachuan Zhao +4

Byte-Pair Encoding (BPE) has become a widely adopted subword tokenization method in modern language models due to its simplicity and strong empirical performance across downstream…

cs.CL2025

BLEUBERI: BLEU is a surprisingly effective reward for instruction following

Yapei Chang, Yekyung Kim, Michael Krumdick +4

Reward models are central to aligning LLMs with human preferences, but they are costly to train, requiring large-scale human-labeled preference data and powerful pretrained LLM bac…

cs.CL2025

Boundless Byte Pair Encoding: Breaking the Pre-tokenization Barrier

Craig W. Schmidt, Varshini Reddy, Chris Tanner +1

Pre-tokenization, the initial step in many modern tokenization pipelines, segments text into smaller units called pretokens, typically splitting on whitespace and punctuation. Whil…

cs.CL2025

How Much is Enough? The Diminishing Returns of Tokenization Training Data

Varshini Reddy, Craig W. Schmidt, Yuval Pinter +1

Tokenization, a crucial initial step in natural language processing, is governed by several key parameters, such as the tokenization algorithm, vocabulary size, pre-tokenization st…