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As generative models and AI agents propose chemical reactions at a scale beyond expert review, feasibility verifiers decide which proposals enter synthesis planning. But do their decisions agree with chemists across different kinds of candidates? We introduce FREA, a benchmark of 751 reactions labeled by expert chemist...
ARMOR is proposed, an agentic framework that explicitly models tool-specific utilities, adaptively prioritizes tools, and further resolves the potential tool conflicts to produce the final prediction for each reaction.
MMORF is presented, a framework for constructing language model-based multi-agent systems (MAS) for multi-objective retrosynthesis planning that achieves strong safety and cost metrics on soft-constraint tasks, frequently Pareto-dominating baseline routes, and outperforming state-of-the-art baselines.
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