arXiv Artificial Intelligence

KGFR: A Foundation Retriever for Generalized Knowledge Graph Question Answering

8 days ago 02.09.2026 07:00 👁 1 views
KGFR: A Foundation Retriever for Generalized Knowledge Graph Question Answering

Quick summary

arXiv:2511.04093v2 Announce Type: replace Abstract: Large language models (LLMs) excel at reasoning but struggle with knowledge-intensive questions due to limited context and parametric knowledge. However, existing methods that rely on finetuned LLMs or GNN retrievers are limited by dataset-specific tuning and scalability on large or unseen graphs. We propose the LLM-KGFR collaborative framework, where an LLM works with a structured retriever, the Knowledge Graph Foundation Retriever (KGFR). KGFR encodes relations using LLM-generated descriptions and initializes entities based on their roles i

Key takeaways

  • arXiv:2511.04093v2 Announce Type: replace Abstract: Large language models (LLMs) excel at reasoning but struggle with knowledge-intensive questions due to limited context and parametric knowledge.
  • However, existing methods that rely on finetuned LLMs or GNN retrievers are limited by dataset-specific tuning and scalability on large or unseen graphs.
  • We propose the LLM-KGFR collaborative framework, where an LLM works with a structured retriever, the Knowledge Graph Foundation Retriever (KGFR).

Why it matters

“KGFR: A Foundation Retriever for Generalized Knowledge Graph Question Answering” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗