arXiv:2610.37851v1 Announce Type: new Abstract: Existing scientific-agent benchmarks rarely evaluate whether agents can reconstruct the exact molecular structures and generation workflows specified by sequencing protocols, a capability critical for analyzing customized sequencing assays. We introduce LibStructBench, a document-grounded benchmark for reconstructing sequencing-library structures and molecular workflows. Our experiments show that frontier agents often produce approximately correct reconstructions but remain unreliable at exact reconstruction, particularly in molecular-state representation and workflow connectivity. Switching the underlying language model produced larger average performance differences than switching agent harnesses, with a statistically significant difference only for molecular-state reconstruction. Additional knowledge improved oligo-family recovery in a small pilot without improving mean molecular-workflow scores. Autonomous accumulation of procedural rules and cross-protocol examples showed non-monotonic validation performance and no mean held-out molecular-workflow improvement in the tested trajectory. These findings highlight the need for more controlled and verifiable approaches to scientific reasoning about molecular processes in complex experimental protocols.
Evaluating and improving AI agents for sequencing protocol understanding
A new arXiv paper (2610.37851v1) introduces LibStructBench, a document-grounded benchmark for testing whether AI agents can reconstruct the exact sequencing-library structures and molecular workflows specified by sequencing protocols. Experiments found frontier agents often produce approximately correct reconstructions but remain unreliable at exact reconstruction, especially in molecular-state representation and workflow connectivity, and that switching the underlying language model produced larger average performance differences than switching agent harnesses, with a statistically significant difference only for molecular-state reconstruction. The authors conclude the results highlight the need for more controlled and verifiable approaches to scientific reasoning about molecular processes in complex experimental protocols.
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