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		<title>Stable and time-aware explanations for supply-chain forecasts: A lean XAI framework</title>
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				<category><![CDATA[Biology]]></category>
		<category><![CDATA[demand forecasting]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[LightGBM]]></category>
		<category><![CDATA[M5 competition]]></category>
		<category><![CDATA[machine learning interpretability]]></category>
		<category><![CDATA[retail analytics]]></category>
		<category><![CDATA[rolling-origin validation]]></category>
		<category><![CDATA[SHAP]]></category>
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		<category><![CDATA[supply chain forecasting]]></category>
		<category><![CDATA[temporal stability]]></category>
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					<description><![CDATA[A lean XAI framework combining SHAP, SHAPTime, and rolling-origin validation delivers stable, horizon-aware explanations for supply-chain demand forecasts on the M5 Walmart dataset.]]></description>
		
		
		
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