3 papers
cs.CL2025
Hell or High Water: Evaluating Agentic Recovery from External Failures
Andrew Wang, Sophia Hager, Adi Asija +2
As language model agents are applied to real world problems of increasing complexity, they will be expected to formulate plans across large search spaces. If those plans fail for r…
cs.CL2025
BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases
Mathew J. Koretsky, Maya Willey, Owen Bianchi +7
Biomedical researchers increasingly rely on large-scale structured databases for complex analytical tasks. However, current text-to-SQL systems often struggle to map qualitative sc…
cs.CL2025
Hidden in the Haystack: Smaller Needles are More Difficult for LLMs to Find
Owen Bianchi, Mathew J. Koretsky, Maya Willey +7
Large language models (LLMs) face significant challenges with needle-in-ahaystack tasks, where relevant information ("the needle") must be drawn from a large pool of irrelevant con…