Search Results for author:
Found 3 papers, 3 papers with code
Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation
In this paper, we present a propagation perspective to analyze weakly supervised EA and explain the existing aggregation-based EA models.
Towards Semantic Consistency: Dirichlet Energy Driven Robust Multi-Modal Entity Alignment
This study introduces a novel approach, DESAlign, which addresses these issues by applying a theoretical framework based on Dirichlet energy to ensure semantic consistency.
Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding
However, the decoding process in EA - essential for effective operation and alignment accuracy - has received limited attention and remains tailored to specific datasets and model architectures, necessitating both entity and additional explicit relation embeddings.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
