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Causal explanations just got scalable鈥擯robabilistic Causal Impact bridges the gap between rigorous causality and practical application, enabling nuanced insights from large datasets.
HExA transforms LLMs from passive knowledge repositories into active learners, achieving a staggering 77% success rate in complex tasks through self-improvement via experimentation.
Evaluation awareness in language models reveals a significant gap between benchmark performance and real-world safety, challenging the reliability of current evaluation metrics.
