Customer-obsessed science

The evaluation of spoken language understanding (SLU) systems is often restricted to assessing their global performance or examining predefined subgroups of interest. However, a more detailed analysis at the subgroup level has the potential to uncover valuable insights into how speech system performance differs across various subgroups. In this work, we identify biased data subgroups and describe them at

In professional football, the pass rush has become an increasingly important aspect of the game, with pass rushers being some of the top paid defensive players in the league. In spite of the importance of the pass rush, pass rushing statistics only include the final outcomes of a play, e.g., sack and pass-made. They do not capture the dynamics of the pass rush or fine-grained insights throughout a play

Traditionally data-plane measurements have been used to understand application performance and to detect specific impairments with high confidence. Control plane effects on data-plane performance were often incidental findings, especially for operational measurements in traditional IP networks where highly multiplexed streams were serviced by higher speed, highly protected, optical circuits. As we move

Self-supervised representation learning methods have achieved significant success in computer vision and natural language processing (NLP), where data samples exhibit explicit spatial or semantic dependencies. However, applying these methods to tabular data is challenging due to the less pronounced dependencies among data samples. In this paper, we address this limitation by introducing SwitchTab, a novel

Debugging a performance issue in databases is notoriously hard. Wouldn’t it be convenient if there exists an oracle or a co-pilot for every database system which users can query in natural language (NL) — ‘what’s wrong?’, or even better— ‘How to fix it?’. Large Language Models (LLMs), like ChatGPT, seem to be a natural surrogate to this oracle given their ability to answer a wide range of questions by efficiently