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		<title>Fine-Tuned Llama Model Turns Unstructured Farm Data Into a Searchable Knowledge Graph</title>
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		<pubDate>Sat, 10 Oct 2026 09:34:29 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[agronomy]]></category>
		<category><![CDATA[GraphRAG]]></category>
		<category><![CDATA[instruction fine-tuning]]></category>
		<category><![CDATA[Knowledge graph]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[Llama]]></category>
		<category><![CDATA[LoRA]]></category>
		<category><![CDATA[Neo4j]]></category>
		<category><![CDATA[parameter-efficient fine-tuning]]></category>
		<category><![CDATA[Retrieval-Augmented Generation]]></category>
		<category><![CDATA[soybean]]></category>
		<category><![CDATA[triple extraction]]></category>
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					<description><![CDATA[Researchers fine-tuned a Llama model with LoRA to extract agronomic triplets and build a GraphRAG-powered knowledge graph that outperforms standard retrieval on soybean advisory questions.]]></description>
		
		
		
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