110 citations · 264 across the 35 of their papers we have counts for
7 papers · 1 filter
Mixture of Hidden-Dimensions Transformer
Yilong Chen, Junyuan Shang, Zhengyu Zhang +6
Transformer models encounter challenges in scaling hidden dimensions efficiently, as uniformly increasing them inflates computational and memory costs while failing to emphasize th…
Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing
Wenyuan Zhang, Shuaiyi Nie, Jiawei Sheng +4
Large language model (LLM) role-playing has gained widespread attention. Authentic character knowledge is crucial for constructing realistic LLM role-playing agents. However, exist…
LoginMEA: Local-to-Global Interaction Network for Multi-modal Entity Alignment
Taoyu Su, Xinghua Zhang, Jiawei Sheng +2
Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs (MMKGs), whose entities can be associated with relational triples…
IBMEA: Exploring Variational Information Bottleneck for Multi-modal Entity Alignment
Taoyu Su, Jiawei Sheng, Shicheng Wang +3
Multi-modal entity alignment (MMEA) aims to identify equivalent entities between multi-modal knowledge graphs (MMKGs), where the entities can be associated with related images. Mos…
Optimal Transport Guided Correlation Assignment for Multimodal Entity Linking
Zefeng Zhang, Jiawei Sheng, Chuang Zhang +4
Multimodal Entity Linking (MEL) aims to link ambiguous mentions in multimodal contexts to entities in a multimodal knowledge graph. A pivotal challenge is to fully leverage multi-e…
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…
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
Xiaodong Li, Jiawei Sheng, Jiangxia Cao +3
Cross-domain recommendation (CDR) has been proven as a promising way to tackle the user cold-start problem, which aims to make recommendations for users in the target domain by tra…