Bridging Perception and Language: A Systematic Benchmark for LVLMs' Understanding of Amodal Completion Reports

• URL: http://arxiv.org/abs/2507.05799v1
• Date: Tue, 08 Jul 2025 09:06:47 GMT
• Title: Bridging Perception and Language: A Systematic Benchmark for LVLMs' Understanding of Amodal Completion Reports
• Authors: Amane Watahiki, Tomoki Doi, Taiga Shinozaki, Satoshi Nishida, Takuya Niikawa, Katsunori Miyahara, Hitomi Yanaka,
• Abstract summary: We study the inferential abilities of large vision-language models on texts related to amodal completion.<n>Our results indicate that while many LVLMs achieve human-comparable performance overall, their accuracy diverges for certain types of objects being completed.<n>Intriguingly, this disparity emerges only under Japanese prompting, suggesting a deficiency in Japanese-specific linguistic competence among these models.
• Score: 10.925743866700037
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: One of the main objectives in developing large vision-language models (LVLMs) is to engineer systems that can assist humans with multimodal tasks, including interpreting descriptions of perceptual experiences. A central phenomenon in this context is amodal completion, in which people perceive objects even when parts of those objects are hidden. Although numerous studies have assessed whether computer-vision algorithms can detect or reconstruct occluded regions, the inferential abilities of LVLMs on texts related to amodal completion remain unexplored. To address this gap, we constructed a benchmark grounded in Basic Formal Ontology to achieve a systematic classification of amodal completion. Our results indicate that while many LVLMs achieve human-comparable performance overall, their accuracy diverges for certain types of objects being completed. Notably, in certain categories, some LLaVA-NeXT variants and Claude 3.5 Sonnet exhibit lower accuracy on original images compared to blank stimuli lacking visual content. Intriguingly, this disparity emerges only under Japanese prompting, suggesting a deficiency in Japanese-specific linguistic competence among these models.

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