51 citations · 51 across the 2 of their papers we have counts for
4 papers
Fetch Me If You Can: A Comprehensive Analysis of Fetch Metadata
Pedro Bernardo, Alex Ploner, Marco Squarcina +2
Effective server-side defenses against cross-site attacks depend on understanding the context in which browser requests are generated. However, servers often lack the information n…
DeltaZip: Efficient Serving of Multiple Full-Model-Tuned LLMs
Xiaozhe Yao, Qinghao Hu, Ana Klimovic
Fine-tuning large language models (LLMs) greatly improves model quality for downstream tasks. However, serving many fine-tuned LLMs concurrently is challenging due to the sporadic,…
DataPerf: Benchmarks for Data-Centric AI Development
Mark Mazumder, Colby Banbury, Xiaozhe Yao +42
Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, and faithf…
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning
Cedric Renggli, Xiaozhe Yao, Luka Kolar +3
Transfer learning can be seen as a data- and compute-efficient alternative to training models from scratch. The emergence of rich model repositories, such as TensorFlow Hub, enable…