Search Results for author: Liyi Chen

Found 8 papers, 6 papers with code

Weakly Supervised Semantic Segmentation with Boundary Exploration

1 code implementation ECCV 2020 Liyi Chen, Weiwei Wu, Chenchen Fu, Xiao Han, Yuntao Zhang

Weakly supervised semantic segmentation with image-level labels has attracted a lot of attention recently because these labels are already available in most datasets.

Segmentation Weakly supervised Semantic Segmentation +1

AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations

no code implementations26 Mar 2024 Wei Wu, Chao Wang, Dazhong Shen, Chuan Qin, Liyi Chen, Hui Xiong

Collaborative filtering methods based on graph neural networks (GNNs) have witnessed significant success in recommender systems (RS), capitalizing on their ability to capture collaborative signals within intricate user-item relationships via message-passing mechanisms.

Collaborative Filtering Recommendation Systems

McQueen: a Benchmark for Multimodal Conversational Query Rewrite

1 code implementation23 Oct 2022 Yifei Yuan, Chen Shi, Runze Wang, Liyi Chen, Feijun Jiang, Yuan You, Wai Lam

In this paper, we propose the task of multimodal conversational query rewrite (McQR), which performs query rewrite under the multimodal visual conversation setting.

Multi-modal Siamese Network for Entity Alignment

1 code implementation KDD 2022 Liyi Chen, Zhi Li, Tong Xu, Han Wu, Zhefeng Wang, Nicholas Jing Yuan, Enhong Chen

To deal with that problem, in this paper, we propose a novel Multi-modal Siamese Network for Entity Alignment (MSNEA) to align entities in different MMKGs, in which multi-modal knowledge could be comprehensively leveraged by the exploitation of inter-modal effect.

Ranked #7 on Multi-modal Entity Alignment on UMVM-oea-d-w-v1 (using extra training data)

Attribute Contrastive Learning +3

MMEA: Entity Alignment for Multi-Modal Knowledge Graphs

1 code implementation20 Aug 2020 Liyi Chen, Zhi Li, Yijun Wang, Tong Xu, Zhefeng Wang, Enhong Chen

To that end, in this paper, we propose a novel solution called Multi-Modal Entity Alignment (MMEA) to address the problem of entity alignment in a multi-modal view.

Knowledge Graphs Multimodal Deep Learning +1

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