The field of wafer defect analysis is moving towards the development of innovative frameworks and methods for identifying upstream processes responsible for defects. This is driven by the need to address the complexity of modern semiconductor manufacturing, which involves thousands of process steps and variable-length processing routes. Recent work has focused on overcoming the limitations of conventional vector-based regression models and attribution algorithms, such as Shapley values, to provide more accurate and effective defect analysis. Noteworthy papers include: Wafer Defect Root Cause Analysis with Partial Trajectory Regression, which proposes a novel framework for wafer defect root cause analysis. Sequence-Aware Inline Measurement Attribution for Good-Bad Wafer Diagnosis, which introduces a new framework called Trajectory Shapley Attribution for identifying problematic upstream processes.