Papers with adaptive gradient gating(AGG

1 papers
Rare Tokens Degenerate All Tokens: Improving Neural Text Generation via Adaptive Gradient Gating for Rare Token Embeddings (2022.acl-long)

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Challenge: Recent studies have determined that the learned token embeddings of large-scale neural language models are degenerated to be anisotropic with a narrow-cone shape.
Approach: They propose a method to degenerate the learning gradient for rare token embeddings by gating the specific part of the gradient for all tokens during training stage.
Outcome: The proposed method improves the performance of the models but lacks the training dynamics needed to solve the representation degeneration problem.

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