Introducing Adjoint Sampling, a new learning algorithm that trains generative models based on scalar rewards.
Based on theoretical foundations developed by FAIR, Adjoint Sampling leads to a highly scalable practical algorithm, and can become the foundation for further research… pic.twitter.com/RyVVzbEfBj

— AI at Meta (@AIatMeta) 20 mai 2025

Introducing Adjoint Sampling, a new learning algorithm that trains generative models based on scalar rewards.
Based on theoretical foundations developed by FAIR, Adjoint Sampling leads to a highly scalable practical algorithm, and can become the foundation for further research

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