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#machine learning Preprint Oct 2026

MolP2SBench: Do LLMs Really Reason from Molecular Properties to Structure?

Large language models (LLMs) are increasingly used in molecular discovery and structure elucidation, where decisions depend on physical observations. Existing evaluations primarily focus on end-to-end molecular reconstruction, where correct predictions do not necessarily indicate reliance on the supplied properties. We...

Yu-Han Xie, Zhiyi Shi, Ze-Yi Zhang et al. · 0 citations

Learning to Predict Future-Aligned Research Proposals with Language Models

This work reframing proposal generation as a time-sliced scientific forecasting problem, given a research question and inspiring papers available before a cutoff time, and operationalizes this objective with the Future Alignment Score (FAS), computed via retrieval and LLM-based semantic scoring against a held-out futur...

Heng Wang, Pengcheng Jiang, Jiashuo Sun et al. · 5 citations

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