MolQuest: A Benchmark for Agentic Evaluation of Abductive Reasoning in Chemical Structure Elucidation

Researchers introduce MolQuest, a new benchmark for evaluating AI models' ability to perform complex chemical structure elucidation through multi-step reasoning. Even state-of-the-art AI models achieve only 50% accuracy on this real-world scientific task, revealing significant limitations in current AI systems' strategic reasoning capabilities.

• →MolQuest is a novel agent-based evaluation framework that tests AI models on authentic chemical experimental data requiring multi-step iteration.
• →The benchmark reveals major limitations in current AI systems, with even the best models achieving only 50% accuracy.
• →Most AI models perform below 30% threshold on complex scientific reasoning tasks involving molecular structure elucidation.
• →Current scientific AI benchmarks rely too heavily on simple question-answer formats rather than complex multi-turn interactions.
• →The research highlights a critical gap between AI capabilities and requirements for active participation in scientific discovery.