384 citations · 1.2k across the 32 of their papers we have counts for
6 papers · 1 filter
HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training
Qinghao Ye, Guohai Xu, Ming Yan +4
Video-language pre-training has advanced the performance of various downstream video-language tasks. However, most previous methods directly inherit or adapt typical image-language…
DictBERT: Dictionary Description Knowledge Enhanced Language Model Pre-training via Contrastive Learning
Qianglong Chen, Feng-Lin Li, Guohai Xu +3
Although pre-trained language models (PLMs) have achieved state-of-the-art performance on various natural language processing (NLP) tasks, they are shown to be lacking in knowledge…
X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval
Yiwei Ma, Guohai Xu, Xiaoshuai Sun +3
Video-text retrieval has been a crucial and fundamental task in multi-modal research. The development of video-text retrieval has been considerably promoted by large-scale multi-mo…
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
Chenliang Li, Haiyang Xu, Junfeng Tian +12
Large-scale pretrained foundation models have been an emerging paradigm for building artificial intelligence (AI) systems, which can be quickly adapted to a wide range of downstrea…
Shifting More Attention to Visual Backbone: Query-modulated Refinement Networks for End-to-End Visual Grounding
Jiabo Ye, Junfeng Tian, Ming Yan +5
Visual grounding focuses on establishing fine-grained alignment between vision and natural language, which has essential applications in multimodal reasoning systems. Existing meth…
Learning Deep Semantic Model for Code Search using CodeSearchNet Corpus
Chen Wu, Ming Yan
Semantic code search is the task of retrieving relevant code snippet given a natural language query. Different from typical information retrieval tasks, code search requires to bri…