1 citations · 1 across the 10 of their papers we have counts for
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Bolster Hallucination Detection via Prompt-Guided Data Augmentation
Wenyun Li, Zheng Zhang, Dongmei Jiang +1
Large language models (LLMs) have garnered significant interest in AI community. Despite their impressive generation capabilities, they have been found to produce misleading or fab…
DS-Det: Single-Query Paradigm and Attention Disentangled Learning for Flexible Object Detection
Guiping Cao, Xiangyuan Lan, Wenjian Huang +3
Popular transformer detectors have achieved promising performance through query-based learning using attention mechanisms. However, the roles of existing decoder query types (e.g.,…
Cross-DINO: Cross the Deep MLP and Transformer for Small Object Detection
Guiping Cao, Wenjian Huang, Xiangyuan Lan +3
Small Object Detection (SOD) poses significant challenges due to limited information and the model's low class prediction score. While Transformer-based detectors have shown promis…
Open-Det: An Efficient Learning Framework for Open-Ended Detection
Guiping Cao, Tao Wang, Wenjian Huang +3
Open-Ended object Detection (OED) is a novel and challenging task that detects objects and generates their category names in a free-form manner, without requiring additional vocabu…