SO-Bench: A Structural Output Evaluation of Multimodal LLMs
Multimodal large language models (MLLMs) are increasingly deployed in real-world, agentic settings where outputs must not only be correct, but also conform to predefined data schemas. Despite recent progress in structured generation in textual domain, there is still no benchmark that systematically evaluates schema-grounded information extraction and reasoning over visual inputs. In this work, we …
Read more “SO-Bench: A Structural Output Evaluation of Multimodal LLMs”