3 citations · 4 across the 5 of their papers we have counts for
5 papers
Entity-Graph Enhanced Cross-Modal Pretraining for Instance-level Product Retrieval
Xiao Dong, Xunlin Zhan, Yunchao Wei +5
Our goal in this research is to study a more realistic environment in which we can conduct weakly-supervised multi-modal instance-level product retrieval for fine-grained product c…
elBERto: Self-supervised Commonsense Learning for Question Answering
Xunlin Zhan, Yuan Li, Xiao Dong +3
Commonsense question answering requires reasoning about everyday situations and causes and effects implicit in context. Typically, existing approaches first retrieve external evide…
M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining
Xiao Dong, Xunlin Zhan, Yangxin Wu +6
Despite the potential of multi-modal pre-training to learn highly discriminative feature representations from complementary data modalities, current progress is being slowed by the…
Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining
Xunlin Zhan, Yangxin Wu, Xiao Dong +5
Nowadays, customer's demands for E-commerce are more diversified, which introduces more complications to the product retrieval industry. Previous methods are either subject to sing…
REM-Net: Recursive Erasure Memory Network for Commonsense Evidence Refinement
Yinya Huang, Meng Fang, Xunlin Zhan +3
When answering a question, people often draw upon their rich world knowledge in addition to the particular context. While recent works retrieve supporting facts/evidence from commo…