March 5, 2024, 2:43 p.m. | Yuan Wang, Lokesh Kumar Sambasivan, Mingang Fu, Prakhar Mehrotra

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.00861v1 Announce Type: cross
Abstract: Generative AI applications, such as ChatGPT or DALL-E, have shown the world their impressive capabilities in generating human-like text or image. Diving deeper, the science stakeholder for those AI applications are Deep Generative Models, a.k.a DGMs, which are designed to learn the underlying distribution of the data and generate new data points that are statistically similar to the original dataset. One critical question is raised: how can we leverage DGMs into morden retail supply chain …

abstract ai applications applications arxiv capabilities chatgpt cs.ai cs.lg dall dall-e deep generative models dgms generative generative ai applications generative models human human-like image insights learn pivoting retail science stakeholder supply chain survey taxonomy text type world

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