Papers with Diagnosing fine-grained hallucinations

1 papers
K-GIP: Diagnosing Logical Fractures in Large Vision-Language Models via Verification Scene Graphs and Sequential Pruning (2026.findings-acl)

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Challenge: Existing benchmarks that treat hallucinations as isolated errors neglect causal dependencies between visual perception and textual reasoning.
Approach: They propose a Knowledge-Guided In-Context Probing framework that constructs a dual-perception ground truth to transform abstract priors into multi-granularity queries.
Outcome: The proposed framework isolates deep reasoning failures from simple perceptual misses.

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