125 citations · 326 across the 20 of their papers we have counts for
6 papers · 1 filter
SimViT: Exploring a Simple Vision Transformer with sliding windows
Gang Li, Di Xu, Xing Cheng +2
Although vision Transformers have achieved excellent performance as backbone models in many vision tasks, most of them intend to capture global relations of all tokens in an image…
K-AID: Enhancing Pre-trained Language Models with Domain Knowledge for Question Answering
Fu Sun, Feng-Lin Li, Ruize Wang +3
Knowledge enhanced pre-trained language models (K-PLMs) are shown to be effective for many public tasks in the literature but few of them have been successfully applied in practice…
Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss
Xing Cheng, Hezheng Lin, Xiangyu Wu +2
Employing large-scale pre-trained model CLIP to conduct video-text retrieval task (VTR) has become a new trend, which exceeds previous VTR methods. Though, due to the heterogeneity…
MlTr: Multi-label Classification with Transformer
Xing Cheng, Hezheng Lin, Xiangyu Wu +5
The task of multi-label image classification is to recognize all the object labels presented in an image. Though advancing for years, small objects, similar objects and objects wit…
CAT: Cross Attention in Vision Transformer
Hezheng Lin, Xing Cheng, Xiangyu Wu +5
Since Transformer has found widespread use in NLP, the potential of Transformer in CV has been realized and has inspired many new approaches. However, the computation required for…
Dual-View Distilled BERT for Sentence Embedding
Xingyi Cheng
Recently, BERT realized significant progress for sentence matching via word-level cross sentence attention. However, the performance significantly drops when using siamese BERT-net…