{"ID":2869755,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.19347","arxiv_id":"2509.19347","title":"Characterizing Knowledge Graph Tasks in LLM Benchmarks Using Cognitive Complexity Frameworks","abstract":"Large Language Models (LLMs) are increasingly used for tasks involving Knowledge Graphs (KGs), whose evaluation typically focuses on accuracy and output correctness. We propose a complementary task characterization approach using three complexity frameworks from cognitive psychology. Applying this to the LLM-KG-Bench framework, we highlight value distributions, identify underrepresented demands and motivate richer interpretation and diversity for benchmark evaluation tasks.","short_abstract":"Large Language Models (LLMs) are increasingly used for tasks involving Knowledge Graphs (KGs), whose evaluation typically focuses on accuracy and output correctness. We propose a complementary task characterization approach using three complexity frameworks from cognitive psychology. Applying this to the LLM-KG-Bench f...","url_abs":"https://arxiv.org/abs/2509.19347","url_pdf":"https://arxiv.org/pdf/2509.19347v1","authors":"[\"Sara Todorovikj\",\"Lars-Peter Meyer\",\"Michael Martin\"]","published":"2025-09-17T08:15:14Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}