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New agent RxnMiner automates chemistry reaction data extraction from figures

By PulseAugur Editorial · [1 sources] ·

Researchers have developed RxnMiner, a multimodal agent designed to extract structured reaction data from chemistry figures, a task that previously required significant manual effort. This system integrates molecular recognition and evidence association to reconstruct reaction records, even when indirectly specified. RxnMiner, utilizing Qwen3.8 Flash-Next as its backbone, achieved a significant improvement in stereochemistry-aware reaction macro-F1 scores, raising it from 21.0% to 71.0% on the new ChemRxn-Bench benchmark. This benchmark comprises 603 reaction figures with over 8,500 annotated reaction records, and RxnMiner's performance notably surpasses existing extraction systems. AI

IMPACT Automates complex data extraction from scientific literature, potentially accelerating research in chemistry and related fields.

RANK_REASON The item describes a new research paper introducing a novel agent and benchmark for a specific scientific domain. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New agent RxnMiner automates chemistry reaction data extraction from figures

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  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    RxnMiner: A Multimodal Agent for Structured Reaction Data Extraction from Chemistry Figures

    Reaction data underpin machine learning for reaction prediction, condition recommendation, and retrosynthetic planning, yet extracting these data from literature figures still requires substantial manual effort. Many figures encode multiple experiments through shared templates, s…

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