Review
Aug 2026
Profiling What Matters: Context-Aware Item Profiles from Large-Scale Metadata for LLM Recommenders
While Large Language Models (LLMs) have significantly advanced reranking in recommendation, effectively leveraging item-side information remains challenging. Real-world items are described by vast, heterogeneous, and unstructured metadata, where decision-relevant signals are often implicit, noisy, or buried in long des...
Dojun Hwang, Seunghan Lee, Cheonyoung Park et al.
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