YARD is a training-free method using Y-shaped decoder architecture and register tokens to improve contrastive decoding for hallucination reduction in LVLMs with lower latency.
arXiv preprint arXiv:2510.02790 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Fox detects risky attention heads in LVLMs using visual attention entropy and severs hallucination shortcuts via numerical logit saturation and conflict-gated decoding, outperforming prior methods by 29.1%.
citing papers explorer
-
YARD: Y-Architecture Register Decoding for Efficient Hallucination Mitigation in Large Vision-Language Models
YARD is a training-free method using Y-shaped decoder architecture and register tokens to improve contrastive decoding for hallucination reduction in LVLMs with lower latency.
-
Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding
Fox detects risky attention heads in LVLMs using visual attention entropy and severs hallucination shortcuts via numerical logit saturation and conflict-gated decoding, outperforming prior methods by 29.1%.