4 papers
Interactive Multi-Objective Probabilistic Preference Learning with Soft and Hard Bounds
Edward Chen, Sang T. Truong, Natalie Dullerud +2
High-stakes decision-making involves navigating multiple competing objectives with expensive evaluations. For instance, in brachytherapy, clinicians must balance maximizing tumor c…
Metric Match: A Subset Selection Approach to Evaluating LLM Judge Reliability
Alyssa Unell, Natalie Dullerud, Naomi Boneh +4
LLM judges are used to reduce the need for costly human labor in evaluating open-ended text generation. However, the reliability of these judges depends critically on their alignme…
Modeling Multi-Objective Tradeoffs with Monotonic Utility Functions
Edward Chen, Natalie Dullerud, Thomas Niedermayr +5
Countless science and engineering applications in multi-objective optimization (MOO) necessitate that decision-makers (DMs) select a Pareto-optimal (PO) solution which aligns with…
ALMo: Interactive Aim-Limit-Defined, Multi-Objective System for Personalized High-Dose-Rate Brachytherapy Treatment Planning and Visualization for Cervical Cancer
Edward Chen, Natalie Dullerud, Pang Wei Koh +4
In complex clinical decision-making, clinicians must often track a variety of competing metrics defined by aim (ideal) and limit (strict) thresholds. Sifting through these high-dim…