Correlations of model rankings across benchmark dimensions, instances, and math benchmarks show substantial redundancy, with rank correlations saturating at around 50% of instances in most benchmarks.
It is defined as: SRCC = 1 − 6 Pn i=1 d2 i n(n2 − 1) , where: di = rank(xi) − rank(yi), and n is the number of data points
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Redundancy Principles for MLLMs Benchmarks
Correlations of model rankings across benchmark dimensions, instances, and math benchmarks show substantial redundancy, with rank correlations saturating at around 50% of instances in most benchmarks.