Visual interventions provide a training-free way to reduce hallucinations in multimodal large language models. However, an intervention may have little leverage at some layers and may damage a correct answer even when it changes the output. We investigate where visual interventions retain leverage and when they improve...
Qi-Ji Zhou, Jun-Yi Hu, Pei-Yu Wang et al.· 0 citations
This work introduces LAGO (LAnguage-Guided adaptive Object-region focus), which reframes localized recognition as language-guided directed region discovery and addresses the circular dependence between recognizing a class and locating its supporting evidence, while preserving complementary local, contextual, and global...
Jun-Yi Hu, Qiji Zhou, Lei Zhang et al.· arXiv.org· 0 citations
An expert-validated benchmark for multi-aspect, full-paper retrieval that evaluates whether retrievers can consistently recover the same paper from queries targeting its motivation, method, and experimental findings, and proposes MAPLE-Synth, a retrieval-based in-context learning pipeline that leverages OpenReview disc...
Yiyang Wei, Fang Guo, Qiji Zhou et al.· 0 citations
This study proposes a novel Triospect Detection Framework by using additional perspectives of content and expression within a given text to enhance detection reliability against attacks.
