4 papers
Unified Multi-Dimensional Benchmark for Complex Graph Reasoning in Large Language Models
Fali Wang, Ali Al-Lawati, Iliyas Bektas +5
Graph reasoning provides a promising testbed for evaluating the reasoning ability of large language models (LLMs), as graph instances can be programmatically generated, structurall…
Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking
Liangliang Zhang, Zhuorui Jiang, Hongliang Chi +8
Knowledge Graph Question Answering (KGQA) systems rely on high-quality benchmarks to evaluate complex multi-hop reasoning. However, despite their widespread use, popular datasets s…
Towards Graph Foundation Models: A Transferability Perspective
Yuxiang Wang, Wenqi Fan, Suhang Wang +1
In recent years, Graph Foundation Models (GFMs) have gained significant attention for their potential to generalize across diverse graph domains and tasks. Some works focus on Doma…
Graph-based Molecular In-context Learning Grounded on Morgan Fingerprints
Ali Al-Lawati, Jason Lucas, Zhiwei Zhang +2
In-context learning (ICL) effectively conditions large language models (LLMs) for molecular tasks, such as property prediction and molecule captioning, by embedding carefully selec…