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Yoonpyo Lee

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#machine learning Preprint Sep 2026

A foundation model for energy and radiation systems built on heterogeneous scientific interfaces

Scientific foundation models are commonly evaluated after heterogeneous physical problems have already been translated into a compatible gridded, tokenized or symbolic representation. This leaves the scientific interface outside both the pretrained model and the audit of what is actually reused. We study the complement...

Samrendra Roy, Tapas Tripura, Yoonpyo Lee et al. · 0 citations
Preprint Aug 2026

Falsehood and Impossibility Are Different Directions in an AI's Representation of Language

An exploratory activation study of the multimodal open-weight model Gemma 3 4B IT using 85 prompts from 17 philosophical families and a topic-matched modality set of 15 topics, which finds necessary falsehoods are not extreme cases of contingent falsehood but lie closer to the experimentally defined category of semanti...

Yoonpyo Lee · 0 citations
Preprint Jul 2026

Multimodal Language Models Benchmarked Against the NRC Reactor Operator Licensing Examination: Fine-Tuning and Retrieval Strategies

Competence claims for a language model in a safety-critical domain are credible when measured against a standard the domain already enforces. We evaluate an open-weight 31-billion-parameter multimodal model (Gemma 4 31B-IT) on the U.S. Nuclear Regulatory Commission Reactor Operator Generic Fundamentals Examination (GFE...

Isak Hwang, Yoonpyo Lee, Syed Bahauddin Alam · 0 citations

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