Debate On Graph Reliable And Adaptive Reasoning Of

# Debate-on-Graph: Reliable and Adaptive Reasoning of Large Language Model on Uncertain Knowledge Graph

Derived from arXiv:2607.17266 - Debate-on-Graph: Reliable and Adaptive Reasoning of Large Language Model on Uncertain Knowledge Graph

## Core Concept
Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing. However, LLMs often suffer from hallucinations and lack of relevant knowledge when dealing with question answering (QA) tasks. To mitigate these issues, knowledge graphs (KGs) have been utilized to enhance LLM reasoning. Nevertheless, KGs often contain noise and errors, while existing KG-enhanced LLM approaches are generally unable to identify and filter such noisy and erroneous content, which ...

## Key Insights
- Derived from arXiv:2607.17266
- Published: 2026-07-19
- Utility Score: 1.00
- Authors: Peiji Yu, Xin Chen, Tianxing Wu

## Activation
debate-on-graph-reliable-and-adaptive-reasoning-of, 2607.17266

## References
- arXiv: https://arxiv.org/abs/2607.17266