12 citations · 32 across the 7 of their papers we have counts for
7 papers
ELIP: Efficient Discriminative Language-Image Pre-training with Fewer Vision Tokens
Yangyang Guo, Haoyu Zhang, Yongkang Wong +2
Learning a versatile language-image model is computationally prohibitive under a limited computing budget. This paper delves into the \emph{efficient language-image pre-training},…
Distance Matters in Human-Object Interaction Detection
Guangzhi Wang, Yangyang Guo, Yongkang Wong +1
Human-Object Interaction (HOI) detection has received considerable attention in the context of scene understanding. Despite the growing progress on benchmarks, we realize that exis…
Rethinking Attention-Model Explainability through Faithfulness Violation Test
Yibing Liu, Haoliang Li, Yangyang Guo +3
Attention mechanisms are dominating the explainability of deep models. They produce probability distributions over the input, which are widely deemed as feature-importance indicato…
OneStop QAMaker: Extract Question-Answer Pairs from Text in a One-Stop Approach
Shaobo Cui, Xintong Bao, Xinxing Zu +4
Large-scale question-answer (QA) pairs are critical for advancing research areas like machine reading comprehension and question answering. To construct QA pairs from documents req…
Answer Questions with Right Image Regions: A Visual Attention Regularization Approach
Yibing Liu, Yangyang Guo, Jianhua Yin +3
Visual attention in Visual Question Answering (VQA) targets at locating the right image regions regarding the answer prediction, offering a powerful technique to promote multi-moda…
Quantifying and Alleviating the Language Prior Problem in Visual Question Answering
Yangyang Guo, Zhiyong Cheng, Liqiang Nie +3
Benefiting from the advancement of computer vision, natural language processing and information retrieval techniques, visual question answering (VQA), which aims to answer question…