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Robust Data Valuation with Weighted Banzhaf Values
We summarize our contributions as follows: 1.
Multi-language Diversity Benefits Autoformalization
Autoformalization is the task of translating natural language materials into machine-verifiable formalisations. Progress in autoformalization research is hindered by the lack of a sizeable dataset consisting of informal-formal pairs expressing the same essence.
How a student becomes a teacher: learning and forgetting through Spectral methods
The above scheme proves particularly relevant when the student network is overparameterized (namely, when larger layer sizes are employed) as compared to the underlying teacher network. Under these operating conditions, it is tempting to speculate that the student ability to handle the given task could be eventually stored in a sub-portion of the whole network.
How a student becomes a teacher: learning and forgetting through Spectral methods
The above scheme proves particularly relevant when the student network is overparameterized (namely, when larger layer sizes are employed) as compared to the underlying teacher network. Under these operating conditions, it is tempting to speculate that the student ability to handle the given task could be eventually stored in a sub-portion of the whole network.
MALL T
Among all the contributing factors, the quality and selection of data is becoming increasingly recognized for its importance in training LLMs effectively.