Llamarine: Open-source Maritime Industry-specific Large Language Model

2025-02-28

AI Summary

To address the insufficient domain-specific reasoning capabilities of general-purpose large language models (LLMs) in maritime navigation, this paper introduces Llamarine—the first open-source large language model specifically designed for marine navigation. Methodologically, we employ continual pretraining and supervised fine-tuning on a high-quality, domain-specific corpus comprising maritime textbooks, peer-reviewed academic papers, and authoritative online resources, and propose the first dedicated benchmark for maritime decision-making evaluation. Key contributions include: (1) releasing the first open-source foundational maritime LLM; (2) establishing a systematic, high-fidelity maritime corpus infrastructure; and (3) introducing a reproducible domain-adaptation paradigm. Experimental results demonstrate that Llamarine significantly outperforms both general-purpose and commercial LLMs on trajectory planning, collision-risk assessment, and compliance with international maritime regulations—validating the effectiveness and necessity of domain-specialized modeling.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Planning, Routing, and Scheduling: Planning with Language Models
• Application Domains: Transportation

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Search Tool Learning with LLM: Teaching LLMs to invoke search and make use of retrieved information

Abstract

Large Language Models (LLMs) have demonstrated substantial potential in addressing complex reasoning tasks, yet their general-purpose nature often limits their effectiveness in specialized domains such as maritime navigation. To bridge this gap, we introduce Llamarine, the first open-source LLM designed specifically for maritime navigation. Llamarine 1.0 is developed through continued pretraining and fine-tuning on a high-quality corpus comprising maritime textbooks, research publications, and web text from Wikipedia. This domain-specific training enables the model to acquire expert-level knowledge in navigational principles, collision avoidance, route optimization, and regulatory compliance. Our key contributions include (a) the curation of a comprehensive maritime dataset from authoritative sources, ensuring depth and reliability in the model's knowledge base; (b) the development of a foundational model capable of reasoning about complex navigational challenges with greater accuracy than general-purpose LLMs; and (c) the establishment of a benchmark to evaluate performance in maritime-specific decision-making tasks. Experimental results demonstrate that Llamarine outperforms both general-purpose and commercial LLMs in critical navigation-related tasks, such as trajectory planning, risk assessment, and compliance with maritime regulations. By providing an open-source foundation model trained exclusively on high-quality maritime literature, Llamarine paves the way for AI-driven advancements in maritime safety, efficiency, and operational decision-making.

Problem

• Develops Llamarine, an open-source LLM for maritime navigation.
• Enhances accuracy in navigational tasks like route optimization.
• Establishes benchmarks for maritime-specific decision-making performance.

Innovation

• Domain-specific LLM for maritime navigation
• Continued pretraining on maritime literature
• Open-source model for maritime decision-making