activity
20242026
most citedApproximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings

1 citations · 1 across the 9 of their papers we have counts for

collaborators
Showing cs.AIShow all

14 papers · 1 filter

cs.AI2026

SCAIR: Schema-Conditioned Agentic Iterative Reasoning for Enterprise Knowledge Graphs

Prateek Chaturvedi, Yuqicheng Zhu, Hongkuan Zhou +6

Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) enables natural language interaction with structured enterprise knowledge, yet existing agentic approaches that perfor…

cs.AI20261 cited

Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings

Yuqicheng Zhu, Nico Potyka, Bo Xiong +4

Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be used to approximate probabilisti…

cs.AI2026

KAPPS: A knowledge-based CPPS Architecture for the Circular Factory

Etienne Hoffmann, Jan-Felix Klein, Sören Weindel +7

While linear manufacturing relies on homogeneous materials and predefined process sequences, circular manufacturing reintroduces used products with heterogeneous and uncertain cond…

cs.AI2026

What Breaks Knowledge Graph based RAG? Benchmarking and Empirical Insights into Reasoning under Incomplete Knowledge

Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang +5

Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) is an increasingly explored approach for combining the reasoning capabilities of large language models with the struct…

cs.AI2025

Geometric Structural Knowledge Graph Foundation Model

Ling Xin, Mojtaba Nayyeri, Zahra Makki Nayeri +1

Structural knowledge graph foundation models aim to generalize reasoning to completely new graphs with unseen entities and relations. A key limitation of existing approaches like U…

cs.AI2025

GR-Agent: Adaptive Graph Reasoning Agent under Incomplete Knowledge

Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang +5

Large language models (LLMs) achieve strong results on knowledge graph question answering (KGQA), but most benchmarks assume complete knowledge graphs (KGs) where direct supporting…