DBES supplies a multi-domain benchmark and five metrics (Routing Specialization, Normalized Effective Rank, Domain Isolation, Routing Stiffness Score, N-gram Expertise) that reveal distinct specialization patterns across MoE models and enable 66-94% domain gains with 15% training resources.
SWE-bench: Can language models resolve real-world github issues? In The Twelfth International Conference on Learning Representations, 2024
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DBES: A Systematic Benchmark and Metric Suite for Evaluating Expert Specialization in Large-Scale MoEs
DBES supplies a multi-domain benchmark and five metrics (Routing Specialization, Normalized Effective Rank, Domain Isolation, Routing Stiffness Score, N-gram Expertise) that reveal distinct specialization patterns across MoE models and enable 66-94% domain gains with 15% training resources.