38 citations · 81 across the 6 of their papers we have counts for
6 papers
DiSTRICT: Dialogue State Tracking with Retriever Driven In-Context Tuning
Praveen Venkateswaran, Evelyn Duesterwald, Vatche Isahagian
Dialogue State Tracking (DST), a key component of task-oriented conversation systems, represents user intentions by determining the values of pre-defined slots in an ongoing dialog…
A No-Code Low-Code Paradigm for Authoring Business Automations Using Natural Language
Michael Desmond, Evelyn Duesterwald, Vatche Isahagian +1
Most business process automation is still developed using traditional automation technologies such as workflow engines. These systems provide domain specific languages that require…
Increasing the Speed and Accuracy of Data LabelingThrough an AI Assisted Interface
Michael Desmond, Zahra Ashktorab, Michelle Brachman +8
Labeling data is an important step in the supervised machine learning lifecycle. It is a laborious human activity comprised of repeated decision making: the human labeler decides w…
Towards Automating the AI Operations Lifecycle
Matthew Arnold, Jeffrey Boston, Michael Desmond +5
Today's AI deployments often require significant human involvement and skill in the operational stages of the model lifecycle, including pre-release testing, monitoring, problem di…
One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers
Matthew Halpern, Behzad Boroujerdian, Todd Mummert +2
Today's cloud service architectures follow a "one size fits all" deployment strategy where the same service version instantiation is provided to the end users. However, consumers a…
Exploring the Hyperparameter Landscape of Adversarial Robustness
Evelyn Duesterwald, Anupama Murthi, Ganesh Venkataraman +2
Adversarial training shows promise as an approach for training models that are robust towards adversarial perturbation. In this paper, we explore some of the practical challenges o…