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From: DIVE-to-design: how a multi-agent workflow converts figure-centric literature into an ai-native hydrogen storage discovery engine

Figure 1. Overview of the DIVE workflow and its evaluation. (A) Conventional single-model pipeline for multimodal extraction; (B) DIVE pipeline: key figure information is first converted into descriptive text prompts, then used for structured data extraction. PCT refers to pressure-composition-temperature curves, and TPD refers to temperature-programmed desorption curves; (C) Batch-evaluation strategy for extraction quality. AI outputs and human annotations are both represented as lists of dictionaries; a shared embedding model aligns matched fields, and the aligned numeric entries are used to compute accuracy and completeness. DIVE: Descriptive Interpretation of Visual Expression; PCT: pressure-composition-temperature; TPD: temperature-programmed desorption; AI: artificial intelligence.