Astana time
AI QAZAQSTANKZ · AIBeta

Smart portal about artificial intelligence and high technology in Kazakhstan

Research1 min read

From the original source:

arXiv — cs.AI

Read full article at arXiv — cs.AI

This material was compiled from public sources. If its publication affects your rights → Request removal

Detecting Hallucination in LLMs: Tracing the Topological Signatures of Impaired Context Sharing

In this work, we examine the topology of information flow patterns within attention graphs to effectively distinguish hallucinated from non-hallucinated responses. We analyze the Forman-Ricci curvature to identify structural patterns indicating information bottlenecks in…

arXiv — cs.AIBy: Amir Jalilifard, Anderson Rocha, Eric Wong, Marcos Medeiros RaimundoSeptember 22, 2026 (Sep 22)
Available in 1 languages

AI Summary & Key Takeaways

  • In this work, we examine the topology of information flow patterns within attention graphs to effectively distinguish hallucinated from non-hallucinated responses
  • We analyze the Forman-Ricci curvature to identify structural patterns indicating information bottlenecks in…
Research
KZ·AI 6A50
Инсайт дня

Detecting Hallucination in LLMs: Tracing the Topological Signatures of Impaired Context Sharing

Tags:#arXiv
Share:

Related stories

Back to list