We present an updated version of Global Counterfactual-based Visual Explanations (GLOVES), a visualization platform for exploring global counterfactual explanations (GCE), designed to enhance the interpretability of machine learning models at the population level. GLOVES enables users to upload datasets and machine learning models or choose from preloaded options to interactively generate, analyze, and compare counterfactual strategies using diverse GCE algorithms. In this extended version, GLOVES includes two additional GCE algorithms, GLOBE-CE and Group-CF, which broaden the spectrum of supported methods for generating global recourse. We also introduce a comparative view that allows users to visually compare the three supported algorithms based on how they affect the population, in regards to the number of global counterfactual actions generated. Finally, we have refined the look and feel of the interface, improving usability and making key visualizations more accessible and engaging. With these enhancements, GLOVES continues to offer an effective and extensible platform to experiment with and understand global counterfactual explanations in AI-driven decision systems.