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cs.CV2026
Decompose, Compare, and Decide: Multimodal LLMs are Implicit Few-Shot Learners
Yunhan Wang, Eshika Khandelwal, Edson Araujo +3
Multimodal Large Language Models (MLLMs) have demonstrated remarkable abilities when analyzing images, yet translating these capabilities to few-shot image classification remains c…
cs.CV2026
FindIt: A Format-Informed Visual Detection Benchmark for Generalist Multimodal LLMs
Eshika Khandelwal, Jingjing Pan, Mingfang Zhang +3
Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, and summarization. However, t…