MineAgent: Towards Remote-Sensing Mineral Exploration with Multimodal Large Language Models

• URL: http://arxiv.org/abs/2412.17339v1
• Date: Mon, 23 Dec 2024 07:08:14 GMT
• Title: MineAgent: Towards Remote-Sensing Mineral Exploration with Multimodal Large Language Models
• Abstract summary: MineAgent is a framework for multi-image reasoning and spatial-spectral integration.<n>MineBench is a benchmark for evaluating MLLMs in domain-specific mineral exploration tasks.
• Score: 8.668070469135936
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Remote-sensing mineral exploration is critical for identifying economically viable mineral deposits, yet it poses significant challenges for multimodal large language models (MLLMs). These include limitations in domain-specific geological knowledge and difficulties in reasoning across multiple remote-sensing images, further exacerbating long-context issues. To address these, we present MineAgent, a modular framework leveraging hierarchical judging and decision-making modules to improve multi-image reasoning and spatial-spectral integration. Complementing this, we propose MineBench, a benchmark specific for evaluating MLLMs in domain-specific mineral exploration tasks using geological and hyperspectral data. Extensive experiments demonstrate the effectiveness of MineAgent, highlighting its potential to advance MLLMs in remote-sensing mineral exploration.

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