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Robust Failure, Conservative Repair: Textual Knowledge Distillation from Cross-Model Failures
Failure-based textual knowledge distillation aims to discover gaps in a model's knowledge by examining its task errors. The distilled knowledge can be useful for the reasoning of both this model ("source model") and other models. However, this transfer of knowledge may not be stable. We define a rul
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