168 citations · 344 across the 20 of their papers we have counts for
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cs.CL2022★ 2 cited
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Ziqi Wang, Yuexin Wu, Frederick Liu +5
Knowledge distillation is one of the primary methods of transferring knowledge from large to small models. However, it requires massive task-specific data, which may not be plausib…
cs.CL2022★ 3 cited
Towards Tracing Factual Knowledge in Language Models Back to the Training Data
Ekin Akyürek, Tolga Bolukbasi, Frederick Liu +4
Language models (LMs) have been shown to memorize a great deal of factual knowledge contained in their training data. But when an LM generates an assertion, it is often difficult t…