CACM improves language-based drug discovery agents by 36.4% via protocol auditing, a grounded diagnostician, and compressed static/dynamic/corrective memory channels that localize failures and bias corrections.
McNaughton, Gautham Krishna Sankar Ramalaxmi, Agustin Kruel, Carter R
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A planner-executor multi-agent system using gpt-oss-120b and Parsl orchestrates scalable high-throughput MOF screening on the Aurora supercomputer with low overhead.
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Constraint-Aware Corrective Memory for Language-Based Drug Discovery Agents
CACM improves language-based drug discovery agents by 36.4% via protocol auditing, a grounded diagnostician, and compressed static/dynamic/corrective memory channels that localize failures and bias corrections.
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Multi-Agent Orchestration for High-Throughput Materials Screening on a Leadership-Class System
A planner-executor multi-agent system using gpt-oss-120b and Parsl orchestrates scalable high-throughput MOF screening on the Aurora supercomputer with low overhead.