Large Language Models

How LLM-Driven AutoML Can Improve Cross-Lingual Handwritten OCR
A research summary of my ICCKE 2025 paper on LLM-driven AutoML, cross-lingual handwritten OCR, and closed-loop neural architecture search using GPT-5, GPT-4o, and Claude Sonnet 4.
Mobina Kashaniyan
Posted Jul 2, 2026 Research Summary, Artificial Intelligence, Computer Vision
PerfMamba: Performance Analysis and Pruning of Selective State Space Models
Research summary of PerfMamba, a Springer conference paper on performance analysis, runtime profiling, scaling behavior, and pruning of Mamba-1 and Mamba-2 selective state space models.
Mobina Kashaniyan
Posted Jul 2, 2026 Research Summary, Efficient AI, High-Performance Computing, Machine Learning Systems
PerfMamba: Performance Analysis and Pruning of Selective State Space Models
PerfMamba analyzes the runtime behavior, resource utilization, memory access patterns, scaling properties, and pruning opportunities of Mamba-1 and Mamba-2 selective state space models.
Abdullah Al Asif, Mobina Kashaniyan, Sixing Yu, Juan Pablo Muñoz, Ali Jannesari
Posted Jan 1, 2026 Conference Paper, Efficient AI, High-Performance Computing
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LLM-Driven AutoML for Cross-Lingual Handwritten OCR: Closed-Loop Neural Architecture Search with GPT-5, GPT-4o, and Claude Sonnet 4
A fully automated LLM-driven AutoML framework for cross-lingual handwritten OCR using closed-loop neural architecture search with GPT-5, GPT-4o, and Claude Sonnet 4 across Arabic, English, and Persian scripts.
Mobina Kashaniyan, Amirhossein Ghassemi, Nasser Mozayani
Posted Oct 28, 2025 Conference Paper
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