11 papers
Joint Optimization for Greedy Longest-match Tokenization
Adhiraj Singh, Deepanshu Mody, Ghina Al Shdaifat +4
Recent work has shown that subword vocabularies can be trained to optimize compression for a specific inference rule rather than relying on greedy heuristics such as Byte Pair Enco…
The Effect of Scripts and Formats on LLM Numeracy
Varshini Reddy, Craig W. Schmidt, Seth Ebner +3
Large language models (LLMs) have achieved impressive proficiency in basic arithmetic, rivaling human-level performance on standard numerical tasks. However, little attention has b…
Tokenization with Split Trees
Craig W. Schmidt, Michael Krumdick, Adam Wiemerslage +4
We introduce Tokenization with Split Trees (ToaST), a subword tokenization method that directly optimizes compression under a new recursive inference procedure. ToaST greedily spli…
FrontierFinance: A Long-Horizon Computer-Use Benchmark of Real-World Financial Tasks
Michael Krumdick, Varshini Reddy, Shivani Chaudhary +8
As concerns surrounding AI-driven labor displacement intensify in knowledge-intensive sectors, existing benchmarks fail to measure performance on tasks that define practical profes…
No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding
Michael Krumdick, Charles Lovering, Varshini Reddy +2
Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as business and finance. The LLM-as-a-…
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…