3 papers
cs.CL2026
Synthetic Data for any Differentiable Target
Tristan Thrush, Sung Min Park, Herman Brunborg +5
What are the limits of controlling language models via synthetic training data? We develop a reinforcement learning (RL) primitive, the Dataset Policy Gradient (DPG), which can pre…
cs.AI2024
OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale
Ali AhmadiTeshnizi, Wenzhi Gao, Herman Brunborg +3
Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than opt…
cs.LG2024
LABOR-LLM: Language-Based Occupational Representations with Large Language Models
Susan Athey, Herman Brunborg, Tianyu Du +2
This paper builds an empirical model that predicts a worker's next occupation as a function of the worker's occupational history. Because histories are sequences of occupations, th…