Congratualtions!

Our paper has been accepted to the Many Lenses, One World: Culturally-Aware Interactive AI in the Metaverse Workshop at the IEEE International Conference on Image Processing (ICIP) 2026 [LINK]

  • Title: Revealing Hidden Response Ambiguity in Binary Evaluation of Cultural Gesture Understanding

  • Authors: Sunghun Kang, Seungjae Lee, Hongseok Cho, Hyeokjun Kweon, Hak Gu Kim

  • Abstract: Gestures are culturally dependent forms of non-verbal communication whose meanings can vary substantially across regions. Recent benchmarks such as MC-SIGNS evaluate whether vision-language models (VLMs) correctly judge the appropriateness of gestures across cultural contexts, often by parsing responses into binary Yes/No outcomes. However, such binary evaluation can obscure important differences in the underlying response forms. In this paper, we investigate the hidden ambiguity underlying parsed “No” responses in culturally sensitive gesture understanding. We show that identical binary outcomes can arise from fundamentally different response forms, including culturally grounded rejection, over-refusal, and self-contradictory reasoning. To analyze this, we introduce a post-hoc response categorization framework that decomposes parsed “No” responses into interpretable categories using lexical cues in raw outputs. Experiments on three open-weight VLMs show that binary evaluation alone can substantially overestimate culturally informed gesture understanding by conflating valid negative judgments with spurious response forms.