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Zongsheng Cao

7 accepted papers

2026

NumCoKE: Ordinal-Aware Numerical Reasoning over Knowledge Graphs with Mixture-of-Experts and Contrastive Learning

AAAI 2026technical

Knowledge graphs (KGs) serve as a vital backbone for a wide range of AI applications, including natural language understanding and recommendation. A promising yet underexplored direction is numerical reasoning over KGs, which involves inferring new facts by leveraging not only symbolic triples but a

Cited by 0SourcePDFScholar
2026

ViG-RAG: Video-aware Graph Retrieval-Augmented Generation via Temporal and Semantic Hybrid Reasoning

AAAI 2026technical

Retrieval-augmented generation (RAG) has greatly improved Large Language Models (LLMs) by adding external knowledge. However, current RAG-based methods face difficulties with long-context video understanding due to two main challenges. First, Current RAG-based methods for long-context video understa

Cited by 0SourcePDFScholar
2026

VideoTrace-R1: Long Video-based Retrieval-Augmented Generation via Temporal Path Graph Understanding

ICML 2026poster

Long-video temporal reasoning remains challenging for Large Video Language Models (LVLMs). Recent reasoning-enhanced models apply reinforcement learning with outcome supervision to improve temporal understanding. However, outcome-only rewards cannot distinguish whether a model arrived at the correct…

Cited by 0SourceScholar
2022

ER: Equivariance Regularizer for Knowledge Graph Completion

AAAI 2022technical

Tensor factorization and distanced based models play important roles in knowledge graph completion (KGC). However, the relational matrices in KGC methods often induce a high model complexity, bearing a high risk of overfitting. As a remedy, researchers propose a variety of different regularizers suc…

2022

Geometry Interaction Knowledge Graph Embeddings

AAAI 2022technical

Knowledge graph (KG) embeddings have shown great power in learning representations of entities and relations for link prediction tasks. Previous work usually embeds KGs into a single geometric space such as Euclidean space (zero curved), hyperbolic space (negatively curved) or hyperspherical space (…

2022

OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport

NeurIPS 2022accept

Multi-modal knowledge graph embeddings (KGE) have caught more and more attention in learning representations of entities and relations for link prediction tasks. Different from previous uni-modal KGE approaches, multi-modal KGE can leverage expressive knowledge from a wealth of modalities (image, te…

Cited by 72SourcePDFScholar
2021

Dual Quaternion Knowledge Graph Embeddings

AAAI 2021technical

In this paper, we study the problem of learning representations of entities and relations in the knowledge graph for the link prediction task. Our idea is based on the observation that the vast majority of the related work only models the relation as a single geometric operation such as translation…