Rethinking uncertainly missing and ambiguous visual modality in multi-modal entity alignment
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to
identify identical entities across disparate knowledge graphs (KGs) by exploiting associated …
identify identical entities across disparate knowledge graphs (KGs) by exploiting associated …
Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs via Active Learning
Modern Knowledge Graphs (KGs) are inevitably noisy due to the nature of their construction
process. Existing robust learning techniques for noisy KGs mostly focus on triple facts, where …
process. Existing robust learning techniques for noisy KGs mostly focus on triple facts, where …
ReliK: A Reliability Measure for Knowledge Graph Embeddings
Can we assess a priori how well a knowledge graph embedding will perform on a specific
downstream task and in a specific part of the knowledge graph? Knowledge graph …
downstream task and in a specific part of the knowledge graph? Knowledge graph …
DiffusionE: Reasoning on Knowledge Graphs via Diffusion-based Graph Neural Networks
Z Cao, J Li, Z Wang, J Li - Proceedings of the 30th ACM SIGKDD …, 2024 - dl.acm.org
Graph Neural Networks (GNNs) have demonstrated powerful capabilities in reasoning
within Knowledge Graphs (KGs), gathering increasing attention. Our idea stems from the …
within Knowledge Graphs (KGs), gathering increasing attention. Our idea stems from the …
Position-Aware Active Learning for Multi-Modal Entity Alignment
Multi-Modal Entity Alignment (MMEA) aims to identify equivalent entities across different
knowledge graphs by utilizing auxiliary modalities such as images. While MMEA has made …
knowledge graphs by utilizing auxiliary modalities such as images. While MMEA has made …
LLM+ KG@ VLDB'24 Workshop Summary
The unification of large language models (LLMs) and knowledge graphs (KGs) has emerged
as a hot topic. At the LLM+ KG'24 workshop, held in conjunction with VLDB 2024 in …
as a hot topic. At the LLM+ KG'24 workshop, held in conjunction with VLDB 2024 in …
[PDF][PDF] Tabular Embeddings for Tables with Bi-Dimensional Hierarchical Metadata and Nesting
G Shrestha, C Jiang, S Akula, V Yannam, A Pyayt… - EDBT, 2025 - openproceedings.org
Embeddings serve as condensed vector representations for real-world entities, finding
applications in Natural Language Processing (NLP), Computer Vision, and Data …
applications in Natural Language Processing (NLP), Computer Vision, and Data …
Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs
W Yu, J Yang, D Yang - The Web Conference 2024 - openreview.net
Modern Knowledge Graphs (KGs) are inevitably noisy due to the nature of their construction
process. Such noise could significantly impair the performance of link prediction over KGs …
process. Such noise could significantly impair the performance of link prediction over KGs …
[PDF][PDF] NEMO-A Neural, Emotional Architecture for Human-AI Teaming
In this work, we propose a novel architecture for agents to be employed in Human-AI
Teaming in various, even critical, domains based upon affective computing, empathy, and …
Teaming in various, even critical, domains based upon affective computing, empathy, and …
[PDF][PDF] The NEMO co-pilot
In this work, we describe an agent to be employed in Human-AI Teaming in various, even
critical, domains, based upon affective computing, empathy, and Theory of Mind, and a …
critical, domains, based upon affective computing, empathy, and Theory of Mind, and a …