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This paper proposes a Damage Cause Encoder for bridge diagnostic agents that uses knowledge triple extraction from manuals and retrieval-augmented fine-tuning with QLoRA, achieving high accuracy with lower memory usage.
An essay expanding on the metaphor of open source as critical infrastructure by examining how real-world bridges are inspected and maintained, drawing parallels to the need for systematic, government-backed support for open source projects.