Papers with loss-minimising behaviour

1 papers
A Natural Bias for Language Generation Models (2023.acl-short)

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Challenge: a standard probabilistic model for language generation has likely not yet learnt many semantic or syntactic rules of natural language, making it difficult to estimate the probability distribution over next tokens.
Approach: They propose to initialise bias terms in a model's final linear layer with the log-unigram distribution and use it to output the unigram frequency statistics as prior knowledge.
Outcome: The proposed method improves learning efficiency and improves overall performance.

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