Building AI-Orchestrated Pipelines for Large-Scale Reasoning Analysis: How Statistical Modeling Reveals Systematic LLM Unfaithfulness
I built AI evaluation infrastructure that systematically analyzes reasoning patterns across frontier models. Using advanced NLP techniques combined with statistical modeling, the framework enables automated detection of unfaithful reasoning at scale — addressing a critical gap in current evaluation approaches.
Key insight: AI-orchestrated evaluation pipelines can detect systematic unfaithfulness at scale, revealing patterns that manual evaluation methods miss entirely.
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