1 citations · 1 across the 3 of their papers we have counts for
3 papers
Closing the Consistency Gap: Self-Evolving Agents That Learn to Stay on Course
Evelyn Duesterwald, Benjamin Elder, Lilian Ngweta +2
Large language model (LLM)-powered agents can be accurate on average yet unreliable in production, a discrepancy that has been observed but remains largely unaddressed. When given…
Boosting Instruction Following at Scale
Ben Elder, Evelyn Duesterwald, Vinod Muthusamy
A typical approach developers follow to influence an LLM's behavior in an application is through careful manipulation of the prompt, such as by adding or modifying instructions. Ho…
FLOW-BENCH: Towards Conversational Generation of Enterprise Workflows
Evelyn Duesterwald, Siyu Huo, Vatche Isahagian +7
Business process automation (BPA) that leverages Large Language Models (LLMs) to convert natural language (NL) instructions into structured business process artifacts is becoming a…