3 papers
cs.SE2026
LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface
Michael Hind, Basel Shbita, Bo Wu +5
Textual Large Language Models (LLMs) provide a simple and familiar interface: a string of text is used for both input and output. However, the information conveyed to an LLM often…
cs.CL2025
BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks
Anna Sokol, Elizabeth Daly, Michael Hind +4
Large language models (LLMs) are powerful tools capable of handling diverse tasks. Comparing and selecting appropriate LLMs for specific tasks requires systematic evaluation method…
cs.CR2025
Developing a Risk Identification Framework for Foundation Model Uses
David Piorkowski, Michael Hind, John Richards +1
As foundation models grow in both popularity and capability, researchers have uncovered a variety of ways that the models can pose a risk to the model's owner, user, or others. Des…