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Current image restoration models still fail to strike the right balance between noise reduction, detail fidelity, and accurate color in real-world, low-light portrait scenarios, highlighting a critical gap this challenge aims to close.
Solve the cold-start problem in CTR prediction by using multimodal LLMs to generate proxy embeddings that align with existing ID embeddings, enabling effective ranking of new items without usage data.
