most citedUncertainty Quantification and Propagation in Atomistic Machine Learning

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cs.LG2026

Convergence Theory for Iterative LLM-Based Neural Architecture Search: A Parametric Cross-Entropy Framework with Closed-Form Proxy Reliability

Santosh Premi Adhikari, Radu Timofte, Dmitry Ignatov

Large language models (LLMs) are increasingly used as generators in iterative neural architecture search (NAS), yet no formal convergence theory exists for this class of algorithms…

cs.LG2026

Delta-Based Neural Architecture Search: LLM Fine-Tuning via Code Diffs

Santosh Premi Adhikari, Radu Timofte, Dmitry Ignatov

Large language models (LLMs) show strong potential for neural architecture generation, yet existing approaches produce complete model implementations from scratch -- computationall…