Can LLMs Beat Classical Hyperparameter Optimization Algorithms?
This article provides metadata for an academic paper titled 'Can LLMs Beat Classical Hyperparameter Optimization Algorithms?' which explores the efficacy of large language models in machine learning optimization tasks.
Why it matters
The research addresses the potential for AI to automate complex technical processes, which is a major area of interest in computer science.
Focus to learn more arXiv-issued DOI via DataCite Submission history From: Fabio Ferreira [ view email ] [v1] Wed, 25 Mar 2026 17:29:40 UTC (1,874 KB) [v2] Sun, 29 Mar 2026 18:46:53 UTC (2,456 KB) [v3] Sat, 4 Apr 2026 10:33:34 UTC (3,843 KB) [v4] Mon, 13 Apr 2026 21:59:37 UTC (3,768 KB) [v5] Fri, 17 Apr 2026 18:50:51 UTC (3,905 KB) Full-text links: Access Paper: View a PDF of the paper titled Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch, by Fabio Ferreira and 4 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.LG < prev | next > new | recent | 2026-03 Change to browse by: cs stat stat.ML References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
The content is a technical repository entry and lacks any subjective or political framing.
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