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Nishtha N. Vaidya

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#artificial intelligence Preprint Sep 2026

Ontology-Grounded, Reasoner-Verified Benchmarks for Evaluating LLM Reasoning in Scientific AI

Large language models (LLMs) increasingly underpin scientific AI applications that reason over structured knowledge, from biomedical question answering to materials informatics. However, their logical reasoning often falls short, producing factual inaccuracies unacceptable in these settings. Reliable evaluation remains...

Nishtha N. Vaidya, S. Grimm, T. Hubauer et al. · 0 citations
2026

Automatic Chain of Concepts: Conceptual Prompting for LLMs by Constructing Concept Trees

Overall, AutoCoC contributes a reproducible and scalable alternative to expert-authored concept hierarchies by automatically deriving domain-specific prompt structures from documentation, making concept-based prompting more practical for structured knowledge generation.

Hurile Borjigin, Nishtha N. Vaidya, Thomas A. Runkler et al. · 0 citations

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