2025
Measuring What Matters: Evaluating Ensemble LLMs with Label Refinement in Inductive Coding
ACL 2025finding
Inductive coding traditionally relies on labor-intensive human efforts, who are prone to inconsistencies and individual biases. Although large language models (LLMs) offer promising automation capabilities, their standalone use often results in inconsistent outputs, limiting their reliability. In th…