Metadata Reasoner uses agentic LLM reasoning on metadata to select sufficient and minimal data sources, achieving 83.16% F1 on KramaBench and 85.5% F1 on noisy synthetic benchmarks while avoiding low-quality tables 99% of the time.
Autonomous data agents: A new opportunity for smart data
2 Pith papers cite this work. Polarity classification is still indexing.
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A periodic framework is proposed to characterize, compare, and predict behaviors across distributed computing solutions by mapping system properties in a structured space inspired by the chemical periodic table.
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An Agentic Approach to Metadata Reasoning
Metadata Reasoner uses agentic LLM reasoning on metadata to select sufficient and minimal data sources, achieving 83.16% F1 on KramaBench and 85.5% F1 on noisy synthetic benchmarks while avoiding low-quality tables 99% of the time.
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A Periodic Space of Distributed Computing: Vision & Framework
A periodic framework is proposed to characterize, compare, and predict behaviors across distributed computing solutions by mapping system properties in a structured space inspired by the chemical periodic table.