26 citations · 51 across the 6 of their papers we have counts for
6 papers
Towards Fast and Accurate Image-Text Retrieval with Self-Supervised Fine-Grained Alignment
Jiamin Zhuang, Jing Yu, Yang Ding +2
Image-text retrieval requires the system to bridge the heterogenous gap between vision and language for accurate retrieval while keeping the network lightweight-enough for efficien…
MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question Answering
Yang Ding, Jing Yu, Bang Liu +3
Knowledge-based visual question answering requires the ability of associating external knowledge for open-ended cross-modal scene understanding. One limitation of existing solution…
Coarse-to-Careful: Seeking Semantic-related Knowledge for Open-domain Commonsense Question Answering
Luxi Xing, Yue Hu, Jing Yu +2
It is prevalent to utilize external knowledge to help machine answer questions that need background commonsense, which faces a problem that unlimited knowledge will transmit noisy…
Bi-directional Cognitive Thinking Network for Machine Reading Comprehension
Wei Peng, Yue Hu, Luxi Xing +4
We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory. It aims to simulate…
Scene Graph Reasoning with Prior Visual Relationship for Visual Question Answering
Zhuoqian Yang, Zengchang Qin, Jing Yu +1
One of the key issues of Visual Question Answering (VQA) is to reason with semantic clues in the visual content under the guidance of the question, how to model relational semantic…
Semantic Modeling of Textual Relationships in Cross-Modal Retrieval
Jing Yu, Chenghao Yang, Zengchang Qin +3
Feature modeling of different modalities is a basic problem in current research of cross-modal information retrieval. Existing models typically project texts and images into one em…