DPR-BAG generates biomedical abstracts from full texts via BOMRC decomposition, parallel LLM summarization, and refinement, showing higher abstractive novelty than baselines while preserving factual consistency on a 46k-article PMC dataset.
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Robust optimization framework for green ammonia that ensures feasible capacity plans under renewable uncertainty where constraint aggregation fails, using scenario reduction and adaptive policies.
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Divide-Prompt-Refine: a Training-Free, Structure-Aware Framework for Biomedical Abstract Generation
DPR-BAG generates biomedical abstracts from full texts via BOMRC decomposition, parallel LLM summarization, and refinement, showing higher abstractive novelty than baselines while preserving factual consistency on a 46k-article PMC dataset.
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Robust Optimization for Green Ammonia Production
Robust optimization framework for green ammonia that ensures feasible capacity plans under renewable uncertainty where constraint aggregation fails, using scenario reduction and adaptive policies.