CASOP is a new framework that uses a modular algorithm repository, semantic descriptions, and a problem taxonomy to synthesize and evaluate over a million valid optimization pipelines for warehouse order fulfillment across seven benchmarks.
IEEE Access 13, 14010–14028
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Applies PEFT to Florence-2 for GI endoscopy VQA and LoRA-adapted Stable Diffusion 2.1 for synthetic image generation, reporting ROUGE/BLEU gains and image quality metrics on Kvasir-VQA.
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Context-Aware Synthesis of Optimization Pipelines for Warehouse Optimization
CASOP is a new framework that uses a modular algorithm repository, semantic descriptions, and a problem taxonomy to synthesize and evaluate over a million valid optimization pipelines for warehouse order fulfillment across seven benchmarks.
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Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering
Applies PEFT to Florence-2 for GI endoscopy VQA and LoRA-adapted Stable Diffusion 2.1 for synthetic image generation, reporting ROUGE/BLEU gains and image quality metrics on Kvasir-VQA.