3 papers
cs.AI2026
KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering
Yike Wu, Nan Hu, Guilin Qi +11
Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream knowledge-intensive tasks, parti…
cs.CL2026
StressEval: Failure-Driven Dynamic Benchmarking for Knowledge-Intensive Reasoning in Large Language Models
Yongrui Chen, Yangyang Ma, Xiaoying Huang +4
Static benchmarks for LLMs are increasingly compromised by contamination and overfitting especially on knowledge intensive reasoning tasks While recent dynamic benchmarks can allev…
cs.CL2025
Large Language Models Meet Knowledge Graphs for Question Answering: Synthesis and Opportunities
Chuangtao Ma, Yongrui Chen, Tianxing Wu +2
Large language models (LLMs) have demonstrated remarkable performance on question-answering (QA) tasks because of their superior capabilities in natural language understanding and…