arXiv cs.AIPaperClaude Watch
ReTRACE: Feedback-Guided LLM Agent in a Chemistry Harness for Retrosynthesis Planning
This is Claude in a domain where it works: tool-calling on a structured problem with clear ground truth and expert feedback loops. The agent improves through learning from its evaluator, which is exactly how to build robust AI for specialized domains. If you're building domain-specific agents, this is the template: harness the LLM with tools, scorecards, and memory. For chemistry specifically, this is a real step forward.