MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for Knowledge Graph Question Answering

Jul 17, 2026

MARS is a knowledge graph question answering (KGQA) approach that integrates large language models (LLMs) with knowledge graphs without requiring model fine-tuning. It uses a structured retrieval process to iteratively gather relevant information and generate SPARQL queries, adapting the retrieval depth to the question. MARS demonstrates competitive performance on established KGQA benchmarks and is efficient and scalable.

Why it matters: MARS offers a scalable way to improve the reliability of LLMs in knowledge-intensive tasks by grounding answers in explicit, updatable symbolic knowledge without the need for costly fine-tuning.

Full story at: arXiv Computation and Language ↗