Normalized total loss on the Facebook dataset (DCOR with and without RLC). - Hossein Rafieizadeh (22676722) (2025)
To enable a fair visual comparison of training dynamics, each curve is normalized as in Eq (29) by dividing by its epoch-1 value and EMA-smoothed (exponential moving average) with . The EMA is computed as with . This normalization emphasizes relative convergence behavior (shape and stability) rather than raw magnitudes: with RLC, the total objective continues to decrease in late epochs, whereas without RLC it plateaus, consistent with the ablation trends in Table 5.