12 citations · 13 across the 3 of their papers we have counts for
3 papers
econ.TH2025
Incentives for Digital Twins: Task-Based Productivity Enhancements with Generative AI
Catherine Wu, Arun Sundararajan
Generative AI is a technology which depends in part on participation by humans in training and improving the automation potential. We focus on the development of an "AI twin" that…
cs.LG2024★ 1 cited
Planning In Natural Language Improves LLM Search For Code Generation
Evan Wang, Federico Cassano, Catherine Wu +7
While scaling training compute has led to remarkable improvements in large language models (LLMs), scaling inference compute has not yet yielded analogous gains. We hypothesize tha…
cs.CL2024★ 12 cited
A Careful Examination of Large Language Model Performance on Grade School Arithmetic
Hugh Zhang, Jeff Da, Dean Lee +12
Large language models (LLMs) have achieved impressive success on many benchmarks for mathematical reasoning. However, there is growing concern that some of this performance actuall…