13 citations · 26 across the 8 of their papers we have counts for
8 papers
Right this way: Can VLMs Guide Us to See More to Answer Questions?
Li Liu, Diji Yang, Sijia Zhong +4
In question-answering scenarios, humans can assess whether the available information is sufficient and seek additional information if necessary, rather than providing a forced answ…
A Survey on Human-AI Collaboration with Large Foundation Models
Vanshika Vats, Marzia Binta Nizam, Minghao Liu +20
As the capabilities of artificial intelligence (AI) continue to expand rapidly, Human-AI (HAI) Collaboration, combining human intellect and AI systems, has become pivotal for advan…
SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation
Yiqing Wang, Zihan Li, Jieru Mei +7
Recent advancements in large-scale Vision Transformers have made significant strides in improving pre-trained models for medical image segmentation. However, these methods face a n…
Bag of Tricks for FGSM Adversarial Training
Zichao Li, Li Liu, Zeyu Wang +2
Adversarial training (AT) with samples generated by Fast Gradient Sign Method (FGSM), also known as FGSM-AT, is a computationally simple method to train robust networks. However, d…
Unsupervised cross-user adaptation in taste sensation recognition based on surface electromyography with conformal prediction and domain regularized component analysis
Hengyang Wang, Xianghao Zhan, Li Liu +5
Human taste sensation can be qualitatively described with surface electromyography. However, the pattern recognition models trained on one subject (the source domain) do not genera…
CPSC: Conformal prediction with shrunken centroids for efficient prediction reliability quantification and data augmentation, a case in alternative herbal medicine classification with electronic nose
Li Liu, Xianghao Zhan, Xikai Yang +6
In machine learning applications, the reliability of predictions is significant for assisted decision and risk control. As an effective framework to quantify the prediction reliabi…
Classifying herbal medicine origins by temporal and spectral data mining of electronic nose
Li Liu, Xianghao Zhan, Ziheng Duan +6
The origins of herbal medicines are important for their treatment effect, which could be potentially distinguished by electronic nose system. As the odor fingerprint of herbal medi…
Boost AI Power: Data Augmentation Strategies with unlabelled Data and Conformal Prediction, a Case in Alternative Herbal Medicine Discrimination with Electronic Nose
Li Liu, Xianghao Zhan, Rumeng Wu +7
Electronic nose has been proven to be effective in alternative herbal medicine classification, but due to the nature of supervised learning, previous research heavily relies on the…