10 papers
Generating Robust Portfolios of Optimization Models using Large Language Models
Eleni Straitouri, Cheol Woo Kim, Milind Tambe
Mathematical optimization is a powerful tool for structured decision-making across domains such as resource allocation and planning. Formulating optimization models faithful to rea…
Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning
Shresth Verma, Mauricio Tec, Cheol Woo Kim +2
While LLMs excel at single-turn generation, they struggle with long-horizon, multi-turn interactions. Offline reinforcement learning (RL) offers a scalable approach, yet its perfor…
Many Preferences, Few Policies: Towards Scalable Language Model Personalization
Cheol Woo Kim, Jai Moondra, Roozbeh Nahavandi +3
The holy grail of LLM personalization is a single LLM for each user, perfectly aligned with that user's preferences. However, maintaining a separate LLM per user is impractical due…
Incentive-Aware AI Safety via Strategic Resource Allocation: A Stackelberg Security Games Perspective
Cheol Woo Kim, Davin Choo, Tzeh Yuan Neoh +1
As AI systems grow more capable and autonomous, ensuring their safety and reliability requires not only model-level alignment but also strategic oversight of the humans and institu…
Generative AI for Social Impact
Lingkai Kong, Cheol Woo Kim, Davin Choo +1
AI for Social Impact (AI4SI) has achieved compelling results in public health, conservation, and security, yet scaling these successes remains difficult due to a persistent deploym…
Preference Robustness for DPO with Applications to Public Health
Cheol Woo Kim, Shresth Verma, Mauricio Tec +1
We study an LLM fine-tuning task for designing reward functions for sequential resource allocation problems in public health, guided by human preferences expressed in natural langu…