MetaEvaluator meta-learns an initialization from reference models to enable accurate, label-free performance estimation for unseen models across architectures and modalities.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-Learning
MetaEvaluator meta-learns an initialization from reference models to enable accurate, label-free performance estimation for unseen models across architectures and modalities.