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This article explores the performance and scalability challenges of GNNSAT, a learned SAT heuristic, compared to SoftTabu. Through a detailed evaluation on SAT problem distributions, it reveals insights into the limitations and potential improvements of learned algorithms in combinatorial optimization contexts.