AI RESEARCH
SPR-128K: A New Benchmark for Spatial Plausibility Reasoning with Multimodal Large Language Models
arXiv CS.CV
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ArXi:2505.23265v2 Announce Type: replace The performance of image generation has been significantly improved in recent years. However, the study of image screening is rare, and its performance with Multimodal Large Language Models (MLLMs) is unsatisfactory due to the lack of data and the weak spatial plausibility reasoning ability in MLLMs. In this work, we propose a complete solution to address these problems in terms of data and methodology. For data, we collect a comprehensive spatial plausibility reasoning (SPR) dataset with over 128k samples, called SPR-128K.