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cs.CV2025
EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents
Zhili Cheng, Yuge Tu, Ran Li +9
Multimodal Large Language Models (MLLMs) have shown significant advancements, providing a promising future for embodied agents. Existing benchmarks for evaluating MLLMs primarily u…
cs.CV2024
Exploring Perceptual Limitation of Multimodal Large Language Models
Jiarui Zhang, Jinyi Hu, Mahyar Khayatkhoei +2
Multimodal Large Language Models (MLLMs) have recently shown remarkable perceptual capability in answering visual questions, however, little is known about the limits of their perc…