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Found 3 papers, 2 papers with code
$R^3$-NL2GQL: A Hybrid Models Approach for for Accuracy Enhancing and Hallucinations Mitigation
While current NL2SQL tasks constructed using Foundation Models have achieved commendable results, their direct application to Natural Language to Graph Query Language (NL2GQL) tasks poses challenges due to the significant differences between GQL and SQL expressions, as well as the numerous types of GQL.
A Knowledge-based Learning Framework for Self-supervised Pre-training Towards Enhanced Recognition of Biomedical Microscopy Images
Self-supervised pre-training has become the priory choice to establish reliable neural networks for automated recognition of massive biomedical microscopy images, which are routinely annotation-free, without semantics, and without guarantee of quality.
From WSI-level to Patch-level: Structure Prior Guided Binuclear Cell Fine-grained Detection
The coarse detection network is a multi-task detection framework based on circular bounding boxes for cells detection, and central key points for nucleus detection.
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