LLMs GPT-5, GPT-4o, Claude Sonnet 4 automate OCR architecture search

Researchers have developed an automated framework that leverages large language models like GPT-5, GPT-4o, and Claude Sonnet 4 to design neural network architectures for cross-lingual handwritten optical character recognition. These LLMs autonomously generate, train, and refine models, achieving high accuracies above 93 percent on Arabic, Persian, and English datasets. The framework successfully discovered efficient models without manual intervention, demonstrating LLMs' capability as AutoML agents for scalable handwriting recognition. AI

IMPACT Demonstrates LLMs' potential as autonomous agents for complex tasks like neural architecture search, potentially accelerating AI development.

RANK_REASON The cluster contains an academic paper detailing a new methodology for LLM-driven AutoML. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• Claude Sonnet 4
• GPT-4o
• GPT-5
• Mobina Kashaniyan

• paper
• model release

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