4 papers
Explore Separately, Adopt Selectively: Execution-Guided Tool Use over Large Tool Libraries
Anna Mazhar, Seiji Maekawa, Nikita Bhutani
Large language model agents must discover relevant tools from large libraries, e.g., thousands of tools, as new needs arise during task execution. When several candidates could sat…
Trace-Level Analysis of Information Contamination in Multi-Agent Systems
Anna Mazhar, Huzaifa Suri, Sainyam Galhotra
Reasoning over heterogeneous artifacts (PDFs, spreadsheets, slide decks, etc.) increasingly occurs within structured agent workflows that iteratively extract, transform, and refere…
Towards Reliable Testing of Machine Unlearning
Anna Mazhar, Sainyam Galhotra
Machine learning components are now central to AI-infused software systems, from recommendations and code assistants to clinical decision support. As regulations and governance fra…
CAFÉ: Causal Black-Box Testing of Machine Unlearning
Anna Mazhar, Sainyam Galhotra
Machine learning models are increasingly deployed as software components that must evolve as requirements change. When specific training records or features must no longer influenc…