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RetroAgent: Harnessing LLMs to Search Over Structured Memory for Agentic Retrosynthesis Planning
RetroAgent is introduced, an LLM agent that bridges symbolic search and neural reasoning through a harness with structured memory, enabling informed decisions grounded in both global progress and domain knowledge in multi-step retrosynthesis planning.
From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier
It is argued that the next leap in AI4Math systems requires a decisive shift from predefined problem-solvers to research agents that can address frontier mathematical challenges with rigorous formal mathematical reasoning, highlighting core limitations of existing systems in serving as mathematical research agents.