TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling 事件
BREAKTHROUGH2026-05-27影响: HIGH
TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling arXiv:2510.04533v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art image generation but often produce semantic inconsistencies, or hallucinations. Existing inference-time guidance methods rely on external signals or architectural modifications, adding computational overhead. We propose $\mathbf{T}$angential $\mathbf{A}$mplifying $\mathbf{G}$uidance $\mathbf{(TAG)}$, a training-free, architecture-
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TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling
ArXiv CS.CV2026-05-27