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papersTODAY 04:00 UTC

Hybrid 1D-CNN-BiLSTM Framework Proposed for Biomedical Extractive Summarization

Researchers present a hierarchical hybrid model that combines one-dimensional convolutional networks with bidirectional LSTMs to produce extractive summaries of biomedical and clinical text. The approach avoids text generation entirely, sidestepping the factual hallucination risks that make abstractive large language models unreliable in medical settings. The work is posted as a preprint on arXiv.

arXiv Hybrid 1D-CNN-BiLSTM Framework Abstractive summarization Biomedical extractive summarization Clinical text summarization ai-hallucination

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arXiv cs.CLA Hybrid Hierarchical 1D-CNN-BiLSTM Framework for Extractive Summarization of Biomedical and Clinical Text ↗TODAY 04:00 UTC