Large Language Models (LLMs) have unlocked new capabilities and applications; however,
evaluating the alignment with human preferences still poses significant challenges. To …

Web-based applications such as chatbots, search engines and news recommendations
continue to grow in scale and complexity with the recent surge in the adoption of large …

We introduce EQUI-VOCAL: a new system that automatically synthesizes queries over
videos from limited user interactions. The user only provides a handful of positive and …

Abstract Model selection in the context of bandit optimization is a challenging problem, as it
requires balancing exploration and exploitation not only for action selection, but also for …

We consider online model selection with decentralized data over $ M $ clients, and study the
necessity of collaboration among clients. Previous work proposed various federated …

Federated learning is renowned for its efficacy in distributed model training, ensuring that
users, called clients, retain data privacy by not disclosing their data to the central server that …

Web-based applications such as chatbots, search engines and news recommendations
continue to grow in scale and complexity with the recent surge in the adoption of large …

Given a pre-trained classifier and multiple human experts, we investigate the task of online
classification where model predictions are provided for free but querying humans incurs a …

Foundation models have recently expanded into robotics after excelling in computer vision
and natural language processing. The models are accessible in two ways: open-source or …