Mar 29, 2022 · Abstract: When generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text.
In light of this finding, a plethora of decoding strategies have been introduced in the literature, each claiming to generate more desirable text than competing.
Sep 19, 2022 · When generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text.
This work measures changes in attributes of generated text as a function of both decoding strategy and task using human and automatic evaluation.
All texts in our work are generated using Hugging Face's generate method called on a model instance initialized via the from_pretrained method. All generation ...
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When generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text. Yet the properties elicited by various ...
Sep 12, 2024 · When generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text.
Beam search is a go-to strategy for decoding neural sequence models. The algorithm can naturally be viewed as a subset optimization problem, albeit one where ...
Jul 28, 2024 · Decoding strategies dictate how a language model selects the next token in a sequence after predicting probabilities for all possible tokens.
In the case of neural generators, we typically model locally normalized distributions over words at each time step: Neural probabilistic language generators are ...