169 citations · 328 across the 11 of their papers we have counts for
12 papers
A Pre-trained Data Deduplication Model based on Active Learning
Haochen Shi, Xinyao Liu, Fengmao Lv +4
In the era of big data, the issue of data quality has become increasingly prominent. One of the main challenges is the problem of duplicate data, which can arise from repeated entr…
Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training
Yongyi Su, Xun Xu, Tianrui Li +1
Deploying models on target domain data subject to distribution shift requires adaptation. Test-time training (TTT) emerges as a solution to this adaptation under a realistic scenar…
SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation
Huaishao Luo, Junwei Bao, Youzheng Wu +2
Recently, the contrastive language-image pre-training, e.g., CLIP, has demonstrated promising results on various downstream tasks. The pre-trained model can capture enriched visual…
DRAformer: Differentially Reconstructed Attention Transformer for Time-Series Forecasting
Benhan Li, Shengdong Du, Tianrui Li +2
Time-series forecasting plays an important role in many real-world scenarios, such as equipment life cycle forecasting, weather forecasting, and traffic flow forecasting. It can be…
A Differential Attention Fusion Model Based on Transformer for Time Series Forecasting
Benhan Li, Shengdong Du, Tianrui Li
Time series forecasting is widely used in the fields of equipment life cycle forecasting, weather forecasting, traffic flow forecasting, and other fields. Recently, some scholars h…
Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting
Jiabin Tang, Tang Qian, Shijing Liu +3
Accurate traffic forecasting, the foundation of intelligent transportation systems (ITS), has never been more significant than nowadays due to the prosperity of smart cities and ur…
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
Huaishao Luo, Lei Ji, Yanyong Huang +3
Fusion technique is a key research topic in multimodal sentiment analysis. The recent attention-based fusion demonstrates advances over simple operation-based fusion. However, thes…
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
Huaishao Luo, Lei Ji, Ming Zhong +4
Video-text retrieval plays an essential role in multi-modal research and has been widely used in many real-world web applications. The CLIP (Contrastive Language-Image Pre-training…
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension
Huaishao Luo, Yu Shi, Ming Gong +2
Span extraction is an essential problem in machine reading comprehension. Most of the existing algorithms predict the start and end positions of an answer span in the given corresp…
UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
Huaishao Luo, Lei Ji, Botian Shi +6
With the recent success of the pre-training technique for NLP and image-linguistic tasks, some video-linguistic pre-training works are gradually developed to improve video-text rel…
Multi-local Collaborative AutoEncoder
Jielei Chu, Hongjun Wang, Jing Liu +2
The excellent performance of representation learning of autoencoders have attracted considerable interest in various applications. However, the structure and multi-local collaborat…
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
Bin Wang, Jie Lu, Zheng Yan +4
Weather forecasting is usually solved through numerical weather prediction (NWP), which can sometimes lead to unsatisfactory performance due to inappropriate setting of the initial…