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Yanhua Yu

7 accepted papers

2025

LightPROF: A Lightweight Reasoning Framework for Large Language Model on Knowledge Graph

AAAI 2025technical

Large Language Models (LLMs) have impressive capabilities in text understanding and zero-shot reasoning. However, delays in knowledge updates may cause them to reason incorrectly or produce harmful results. Knowledge Graphs (KGs) provide rich and reliable contextual information for the reasoning pro…

2025

R2DQG: A Quality Meets Diversity Framework for Question Generation over Knowledge Bases

IJCAI 2025

The task of Knowledge-Based Question Generation (KBQG) involves generating natural language questions from structured knowledge sources, posing unique challenges in balancing linguistic diversity and semantic relevance. Existing models often focus on maximizing surface-level similarity to ground-tru

2024

Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction

AAAI 2024technical

In recent years, spectral graph neural networks, characterized by polynomial filters, have garnered increasing attention and have achieved remarkable performance in tasks such as node classification. These models typically assume that eigenvalues for the normalized Laplacian matrix are distinct from…

2023

Enhancing Non-line-of-sight Imaging via Learnable Inverse Kernel and Attention Mechanisms

ICCV 2023poster

Recovering information from non-line-of-sight (NLOS) imaging is a computationally-intensive inverse problem. Most physics-based NLOS imaging methods address the complexity of this problem by assuming three-bounce reflections and no self-occlusion. However, these assumptions may break down for object…

Cited by 10PDFcodeScholar
2023

Intent-aware Recommendation via Disentangled Graph Contrastive Learning

IJCAI 2023poster

Graph neural network (GNN) based recommender systems have become one of the mainstream trends due to the powerful learning ability from user behavior data. Understanding the user intents from behavior data is the key to recommender systems, which poses two basic requirements for GNN-based recommende…

2022

Ensemble Multi-Relational Graph Neural Networks

IJCAI 2022poster

It is well established that graph neural networks (GNNs) can be interpreted and designed from the perspective of optimization objective. With this clear optimization objective, the deduced GNNs architecture has sound theoretical foundation, which is able to flexibly remedy the weakness of GNNs. Howe…