Search Results for author:
Found 5 papers, 0 papers with code
Can Contrastive Learning Refine Embeddings
Recent advancements in contrastive learning have revolutionized self-supervised representation learning and achieved state-of-the-art performance on benchmark tasks.
Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs
Through the utilization of both knowledge graph reasoning and LLMs, it successfully derives answers for each subquestion.
Conversational Question Answering with Reformulations over Knowledge Graph
CornNet adopts a teacher-student architecture where a teacher model learns question representations using human writing reformulations, and a student model to mimic the teacher model's output via reformulations generated by LLMs.
Neural Multi-network Diffusion towards Social Recommendation
Graph Neural Networks (GNNs) have been widely applied on a variety of real-world applications, such as social recommendation.
KompaRe: A Knowledge Graph Comparative Reasoning System
In detail, we develop KompaRe, the first of its kind prototype system that provides comparative reasoning capability over large knowledge graphs.
