3 papers
cs.LG2026
Trade-offs in Ensembling, Merging and Routing Among Parameter-Efficient Experts
Sanae Lotfi, Lucas Caccia, Alessandro Sordoni +2
While large language models (LLMs) fine-tuned with lightweight adapters achieve strong performance across diverse tasks, their performance on individual tasks depends on the fine-t…
cs.LG2025
On the Hardness of Bandit Learning
Nataly Brukhim, Aldo Pacchiano, Miroslav Dudik +1
We study the task of bandit learning, also known as best-arm identification, under the assumption that the true reward function f belongs to a known, but arbitrary, function class…
cs.LG2024
A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alexandra Chouldechova +1
Disaggregated evaluation is a central task in AI fairness assessment, where the goal is to measure an AI system's performance across different subgroups defined by combinations of…