2 papers
cs.AI2026
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…
cs.CL2025
Towards LLMs Robustness to Changes in Prompt Format Styles
Lilian Ngweta, Kiran Kate, Jason Tsay +1
Large language models (LLMs) have gained popularity in recent years for their utility in various applications. However, they are sensitive to non-semantic changes in prompt formats…