75 citations · 102 across the 11 of their papers we have counts for
3 papers · 1 filter
Cookbook: A framework for improving LLM generative abilities via programmatic data generating templates
Avanika Narayan, Mayee F. Chen, Kush Bhatia +1
Fine-tuning large language models (LLMs) on instruction datasets is a common way to improve their generative capabilities. However, instruction datasets can be expensive and time-c…
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks
Michael Wornow, Avanika Narayan, Ben Viggiano +15
Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating models on business process management (BPM) tasks. BPM is the practice of documenting, meas…
Automating the Enterprise with Foundation Models
Michael Wornow, Avanika Narayan, Krista Opsahl-Ong +3
Automating enterprise workflows could unlock $4 trillion/year in productivity gains. Despite being of interest to the data management community for decades, the ultimate vision of…