791 citations · 1.5k across the 57 of their papers we have counts for
9 papers · 1 filter
Domain-Guided Conditional Diffusion Model for Unsupervised Domain Adaptation
Yulong Zhang, Shuhao Chen, Weisen Jiang +3
Limited transferability hinders the performance of deep learning models when applied to new application scenarios. Recently, Unsupervised Domain Adaptation (UDA) has achieved signi…
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training
Xinchi Deng, Han Shi, Runhui Huang +7
Cross-modal pre-training has shown impressive performance on a wide range of downstream tasks, benefiting from massive image-text pairs collected from the Internet. In practice, on…
Illumination Controllable Dehazing Network based on Unsupervised Retinex Embedding
Jie Gui, Xiaofeng Cong, Lei He +2
On the one hand, the dehazing task is an illposedness problem, which means that no unique solution exists. On the other hand, the dehazing task should take into account the subject…
Nonparametric Iterative Machine Teaching
Chen Zhang, Xiaofeng Cao, Weiyang Liu +2
In this paper, we consider the problem of Iterative Machine Teaching (IMT), where the teacher provides examples to the learner iteratively such that the learner can achieve fast co…
Effective Structured Prompting by Meta-Learning and Representative Verbalizer
Weisen Jiang, Yu Zhang, James T. Kwok
Prompt tuning for pre-trained masked language models (MLM) has shown promising performance in natural language processing tasks with few labeled examples. It tunes a prompt for the…
A Survey on Time-Series Pre-Trained Models
Qianli Ma, Zhen Liu, Zhenjing Zheng +4
Time-Series Mining (TSM) is an important research area since it shows great potential in practical applications. Deep learning models that rely on massive labeled data have been ut…
No Place to Hide: Dual Deep Interaction Channel Network for Fake News Detection based on Data Augmentation
Biwei Cao, Lulu Hua, Jiuxin Cao +3
Online Social Network (OSN) has become a hotbed of fake news due to the low cost of information dissemination. Although the existing methods have made many attempts in news content…
Fooling the Image Dehazing Models by First Order Gradient
Jie Gui, Xiaofeng Cong, Chengwei Peng +2
The research on the single image dehazing task has been widely explored. However, as far as we know, no comprehensive study has been conducted on the robustness of the well-trained…
Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning
Jidong Ge, Yuxiang Liu, Jie Gui +5
Self-supervised learning enables networks to learn discriminative features from massive data itself. Most state-of-the-art methods maximize the similarity between two augmentations…