Turning GLM-5.3-Flash into a Jev-like decision model

The study transforms GLM-5.3-Flash into a Jev-like decision model, comparing its performance against Jev and Laya across 28 datasets. While a Wilcoxon signed-rank test showed no significant difference (p = 0.64), the number of options impacted accuracy differently. On TREC, Jev dropped from 92.1% to 85.6% with increased options, GLM-5.3-Flash from 91.2% to 79.6%, and Laya from 88.4% to 51.2%. Conversely, on MASSIVE, Jev and GLM-5.3-Flash improved, while Laya declined, indicating task difficulty isn't solely determined by option count.

Unlike previous studies, this report specifically compares GLM-5.3-Flash against Jev and Laya, showing how option count impacts their performance differently across datasets like TREC and MASSIVE.