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Tirthankar Ghosal

2 papers indexed

arxivcs.DCcs.AI2026-07-13

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap

Rafael Ferreira da Silva, Milad Abolhasani, Peter Beaucage, Laura Biven, Michael Bussmann, Kyle Chard, et al.

One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around five critical dimensions. The field has since moved faster than anticipated. Multi-agent systems have produced experimentally valida…

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arxivcs.AIcond-mat.mtrl-scics.CLcs.LG2026-07-01

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination

Subhadeep Pal, Shashwat Sourav, Tirthankar Ghosal, Markus J. Buehler

Accelerating materials discovery requires AI systems that can generate scientifically valid hypotheses through multi-step, domain-grounded reasoning. Standard large language models often produce fluent but weakly traceable responses to open-ended materials design problems, making…

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