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ENTITY Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation

Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation

PulseAugur coverage of Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation — every cluster mentioning Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_239477 ·

    New framework distills LLM reasoning for efficient trade-up recommendations

    Researchers have developed a novel two-level framework for trade-up recommendation that distills large language model (LLM) reasoning into an efficient student model. The first level uses an LLM teacher to generate stru…