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Bridging the Gap Between Understanding and Control: Insights into AI Interpretability
As large language model (LLM) systems grow in complexity, the challenge of ensuring their outputs align with human intentions has become critical. Interpretability—the ability to explain how models reach their decisions—and control—the ability to steer them toward desired outcomes—are two sides of the same coin. “Towards Unifying Interpretability and Control: Evaluation via Intervention”—research by Usha […]