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Introduces Physics-Audited Agentic SciML (PA-SciML), a verification-first workflow where LLM agents discover surrogate models and validate them against physics requirements such as boundary conditions and causality, not just error metrics. Numerical examples show improved trustworthiness over error-only baselines.
This paper proposes Declarative Data Services (DDS), an architecture for structured agentic discovery of data-system compositions from declarative user intent. It decomposes the global search into bounded sub-searches and shows convergence on a trading-backend workload where unbounded discovery fails.
Meta's new paper presents an agentic system that autonomously discovers neural architectures outperforming Llama 3.2 at 350M, 1B, and 3B scales within a 24-hour compute budget.
PolitNuggets is a multilingual benchmark for evaluating large reasoning models within agentic frameworks on their ability to discover and synthesize long-tail political facts by constructing biographies for 400 global elites. The benchmark introduces evaluation protocols like FactNet and reveals that current systems struggle with fine-grained details and efficiency.