View a PDF of the paper titled GSR-BENCH: A Benchmark for Grounded Spatial Reasoning Analysis by way of Multimodal LLMs, by Navid Rajabi and 1 different authors
Summary:The flexibility to grasp and motive about spatial relationships between objects in pictures is a crucial part of visible reasoning. This ability rests on the power to acknowledge and localize objects of curiosity and decide their spatial relation. Early imaginative and prescient and language fashions (VLMs) have been proven to wrestle to acknowledge spatial relations. We lengthen the beforehand launched What’sUp dataset and suggest a novel complete analysis for spatial relationship understanding that highlights the strengths and weaknesses of 27 totally different fashions. Along with the VLMs evaluated in What’sUp, our in depth analysis encompasses 3 lessons of Multimodal LLMs (MLLMs) that fluctuate of their parameter sizes (starting from 7B to 110B), coaching/instruction-tuning strategies, and visible decision to benchmark their performances and scrutinize the scaling legal guidelines on this job.
Submission historical past
From: Navid Rajabi [view email]
[v1]
Wed, 19 Jun 2024 06:15:26 UTC (35,333 KB)
[v2]
Thu, 10 Oct 2024 22:22:52 UTC (35,569 KB)
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#Benchmark #Grounded #Spatial #Reasoning #Analysis #Multimodal #LLMs
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