5 citations · 9 across the 4 of their papers we have counts for
4 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…
Bridging the Gap between Reality and Ideality of Entity Matching: A Revisiting and Benchmark Re-Construction
Tianshu Wang, Hongyu Lin, Cheng Fu +6
Entity matching (EM) is the most critical step for entity resolution (ER). While current deep learningbased methods achieve very impressive performance on standard EM benchmarks, t…
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…