6 citations · 23 across the 9 of their papers we have counts for
9 papers
RMAdapter: Reconstruction-based Multi-Modal Adapter for Vision-Language Models
Xiang Lin, Weixin Li, Shu Guo +2
Pre-trained Vision-Language Models (VLMs), \textit{e.g.} CLIP, have become essential tools in multimodal transfer learning. However, fine-tuning VLMs in few-shot scenarios poses si…
Improving Subgraph Matching by Combining Algorithms and Graph Neural Networks
Shuyang Guo, Wenjin Xie, Ping Lu +5
Homomorphism is a key mapping technique between graphs that preserves their structure. Given a graph and a pattern, the subgraph homomorphism problem involves finding a mapping fro…
Variational Multi-Modal Hypergraph Attention Network for Multi-Modal Relation Extraction
Qian Li, Cheng Ji, Shu Guo +5
Multi-modal relation extraction (MMRE) is a challenging task that aims to identify relations between entities in text leveraging image information. Existing methods are limited by…
Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion
Qian Li, Shu Guo, Yinjia Chen +3
Few-shot knowledge graph completion (FKGC) aims to query the unseen facts of a relation given its few-shot reference entity pairs. The side effect of noises due to the uncertainty…
Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment
Qian Li, Cheng Ji, Shu Guo +3
Multi-Modal Entity Alignment (MMEA) is a critical task that aims to identify equivalent entity pairs across multi-modal knowledge graphs (MMKGs). However, this task faces challenge…
Dual-Gated Fusion with Prefix-Tuning for Multi-Modal Relation Extraction
Qian Li, Shu Guo, Cheng Ji +3
Multi-Modal Relation Extraction (MMRE) aims at identifying the relation between two entities in texts that contain visual clues. Rich visual content is valuable for the MMRE task,…
Deep Structural Point Process for Learning Temporal Interaction Networks
Jiangxia Cao, Xixun Lin, Xin Cong +4
This work investigates the problem of learning temporal interaction networks. A temporal interaction network consists of a series of chronological interactions between users and it…
CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction
Jiawei Sheng, Shu Guo, Bowen Yu +5
Event extraction (EE) is a crucial information extraction task that aims to extract event information in texts. Most existing methods assume that events appear in sentences without…
Bipartite Graph Embedding via Mutual Information Maximization
Jiangxia Cao, Xixun Lin, Shu Guo +3
Bipartite graph embedding has recently attracted much attention due to the fact that bipartite graphs are widely used in various application domains. Most previous methods, which a…