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20222026
most citedMOSABench: Multi-Object Sentiment Analysis Benchmark for Evaluating Multimodal Large Language Models Understanding of Complex Image

1 citations · 1 across the 21 of their papers we have counts for

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cs.CV2026

Seeing Right but Saying Wrong: Inter- and Intra-Layer Refinement in MLLMs without Training

Shezheng Song, Shasha Li, Jie Yu

Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities across a variety of vision-language tasks. However, their internal reasoning often exhibits a critica…

cs.CV2024

MOSABench: Multi-Object Sentiment Analysis Benchmark for Evaluating Multimodal Large Language Models Understanding of Complex Image

Shezheng Song, Chengxiang He, Shan Zhao +4

Multimodal large language models (MLLMs) have shown remarkable progress in high-level semantic tasks such as visual question answering, image captioning, and emotion recognition. H…