New approach for adaptive user representations using diffusion models
In brief
- FINDERS dynamically encodes user behaviors using diffusion models.
- A lightweight router tailors representations to specific scenario needs.
- Tests across ten industrial scenarios show significant performance gains.
The authors introduce FINDERS, a diffusion-based framework to generate dynamic and scenario-adaptive user representations. Unlike existing methods, it leverages the iterative denoising process of dLLMs for multi-granularity reconstruction. Tests across ten industrial scenarios show superior performance compared to current approaches.
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