6 papers
When Is Coarse Supervision Worth It? Cost-Aware Learning under Unknown Aggregation
Jianyu Xu, Smriti Jha, Aarti Singh +1
Modern learning systems often acquire supervision at multiple resolutions, trading annotation cost against information content. We study cost-aware two-resolution learning, where e…
Developing and evaluating a chatbot to support maternal health care
Smriti Jha, Vidhi Jain, Jianyu Xu +8
The ability to provide trustworthy maternal health information using phone-based chatbots can have a significant impact, particularly in low-resource settings where users have low…
Feynman: Knowledge-Infused Diagramming Agent for Scalable Visual Designs
Zixin Wen, Yifu Cai, Kyle Lee +5
Visual design is an essential application of state-of-the-art multi-modal AI systems. Improving these systems requires high-quality vision-language data at scale. Despite the abund…
OEUVRE: OnlinE Unbiased Variance-Reduced loss Estimation
Kanad Pardeshi, Bryan Wilder, Aarti Singh
Online learning algorithms continually update their models as data arrive, making it essential to accurately estimate the expected loss at the current time step. The prequential me…
Online Decision Making with Generative Action Sets
Jianyu Xu, Vidhi Jain, Bryan Wilder +1
With advances in generative AI, decision-making agents can now dynamically create new actions during online learning, but action generation typically incurs costs that must be bala…
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects
Santiago Cortes-Gomez, Naveen Raman, Aarti Singh +1
Randomized controlled trials (RCTs) can be used to generate guarantees on treatment effects. However, RCTs often spend unnecessary resources exploring sub-optimal treatments, which…