Invention Publication
- Patent Title: DISCRETE TOKEN PROCESSING USING DIFFUSION MODELS
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Application No.: US18374447Application Date: 2023-09-28
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Publication No.: US20240119261A1Publication Date: 2024-04-11
- Inventor: Robin Strudel , Rémi Leblond , Laurent Sifre , Sander Etienne Lea Dieleman , Nikolay Savinov , Will S. Grathwohl , Corentin Tallec , Florent Altché , Iaroslav Ganin , Arthur Mensch , Yilin Du
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Main IPC: G06N3/045
- IPC: G06N3/045

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an output sequence of discrete tokens using a diffusion model. In one aspect, a method includes generating, by using the diffusion model, a final latent representation of the sequence of discrete tokens that includes a determined value for each of a plurality of latent variables; applying a de-embedding matrix to the final latent representation of the output sequence of discrete tokens to generate a de-embedded final latent representation that includes, for each of the plurality of latent variables, a respective numeric score for each discrete token in a vocabulary of multiple discrete tokens; selecting, for each of the plurality of latent variables, a discrete token from among the multiple discrete tokens in the vocabulary that has a highest numeric score; and generating the output sequence of discrete tokens that includes the selected discrete tokens.
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