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Found 2 papers, 1 papers with code
SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection
In this paper, we present SpacTor, a new training procedure consisting of (1) a hybrid objective combining span corruption (SC) and token replacement detection (RTD), and (2) a two-stage curriculum that optimizes the hybrid objective over the initial $\tau$ iterations, then transitions to standard SC loss.
Batch Active Learning at Scale
The ability to train complex and highly effective models often requires an abundance of training data, which can easily become a bottleneck in cost, time, and computational resources.
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