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Found 6 papers, 3 papers with code
u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model
Recent advancements in multi-modal large language models (MLLMs) have led to substantial improvements in visual understanding, primarily driven by sophisticated modality alignment strategies.
Open-Set Image Tagging with Multi-Grained Text Supervision
Specifically, for predefined commonly used tag categories, RAM++ showcases 10. 2 mAP and 15. 4 mAP enhancements over CLIP on OpenImages and ImageNet.
Prototype Fission: Closing Set for Robust Open-set Semi-supervised Learning
Instead of "opening set", i. e., modeling OOD distribution, Prototype Fission "closes set" and makes it hard for OOD samples to fit in sub-class latent space.
3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation
With the region proposals from the encoder, we crop multi-level RoI in-region features from the encoder to form a GPU memory-efficient decoder for detailpreserving segmentation and therefore enlarged applicable volume size and effective receptive field.
MONPA: Multi-objective Named-entity and Part-of-speech Annotator for Chinese using Recurrent Neural Network
Part-of-speech (POS) tagging and named entity recognition (NER) are crucial steps in natural language processing.
Incorporating Dependency Trees Improve Identification of Pregnant Women on Social Media Platforms
In this study, we developed a tree kernel-based model to classify tweets conveying pregnancy related information using this corpus.
