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

1. 1Develop a deep understanding of abductive reasoning and its application in chemical structure elucidation
2. 2Design and implement a benchmark that can assess the dynamic reasoning capabilities of large language models
3. 3Evaluate the performance of large language models on the MolQuest benchmark to identify areas for improvement
4. 4Use the insights gained from the benchmark to fine-tune and optimize the models for better performance in real-world research tasks

Researchers and developers working on large language models and chemical structure elucidation can benefit from MolQuest to evaluate and improve model performance in complex scientific tasks

💡 Current scientific evaluation benchmarks are inadequate for measuring model performance in complex scientific tasks, and MolQuest addresses this limitation

🔬 Introducing MolQuest: a benchmark for evaluating abductive reasoning in chemical structure elucidation using LLMs