From the 1 of 4 linked papers with an AI index.
4 papers
Baikal: Structured Search for Deep Research over Data Lakes
Dhruv Agarwal, Rishitha Guttapalle Mohan, Aarti Kumari +5
Baikal is a framework that clusters heterogeneous tables and passages into semantic regions and uses adaptive, budgeted search policies to guide an LLM agent in generating subquest…
Evidence-Informed LLM Beliefs for Continual Scientific Discovery
Dhruv Agarwal, Reece Adamson, Andrew McCallum +3
Open-ended scientific discovery with large language models (LLMs) increasingly operates as a long-horizon loop of hypothesis search and verification, where a reward signal guides w…
AutoDiscovery: Open-ended Scientific Discovery via Bayesian Surprise
Dhruv Agarwal, Bodhisattwa Prasad Majumder, Reece Adamson +8
The promise of autonomous scientific discovery (ASD) hinges not only on answering questions, but also on knowing which questions to ask. Most recent works in ASD explore the use of…
MiGrATe: Mixed-Policy GRPO for Adaptation at Test-Time
Peter Phan, Dhruv Agarwal, Kavitha Srinivas +3
Large language models (LLMs) are increasingly being applied to black-box optimization tasks, from program synthesis to molecule design. Prior work typically leverages in-context le…