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ManGo (Manga Active Narrative Grounding Optimization), an unsupervised framework for active manga visual question answering, introduces Active Narrative Sketching (ANS), which iteratively selects panels, extracts concise grounded clues, and decides when to stop, forming a compact question-directed evidence sketch before answer generation.
A knowledge-verified benchmark that first confirms through a neutral probe that an agent knows a user's entitlement, and then evaluates whether it makes false claims once an incentive to deny that entitlement is introduced, which reduces the confound between lying and not knowing and enables more rigorous auditing and steering of agent honesty.
Safety-aware Contrastive Decoding (SafeCoDe) is introduced, a lightweight and model-agnostic decoding framework that dynamically adjusts token generation based on multimodal context that consistently improves context-sensitive refusal behaviors while preserving model helpfulness.
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