Author

Robby T. Tan

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Preprint Aug 2026

UC-VLM: Consistency-Driven Learning for AI-Generated Image Detection with Vision-Language Large Models

UC-VLM is a unified multi-stage binary-supervised framework that consistently reuses the same authenticity labels for visual adaptation and label-conditioned text generation, while leveraging automatically optimized instructions to reduce prompt sensitivity without requiring human-written rationales or hand-crafted prompts.

Lei Tan, Shuwei Li, Mohan S. Kankanhalli et al. · 0 citations

Preprint Jul 2026

Token-Based Affordance Grounding with Large Vision-Language Models

TokAG, a zero-shot affordance grounding framework that exploits the token-level semantic-spatial signals in LVLMs to localize action-relevant regions without external supervision, and introduces a spatial-aware token-selection mechanism to systematically evaluate each output token.

Seung Il Lee, Qinqian Lei, Daguang Xu et al. · 0 citations