GloRank reformulates list-wise reranking as token generation over a global item identifier space, using supervised pre-training followed by reinforcement learning to maximize list-wise utility and outperforming baselines on benchmarks and industrial data.
McAuley, Christopher Targett, Qinfeng Shi, and Anton van den Hengel
2 Pith papers cite this work. Polarity classification is still indexing.
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From Local Indices to Global Identifiers: Generative Reranking for Recommender Systems via Global Action Space
GloRank reformulates list-wise reranking as token generation over a global item identifier space, using supervised pre-training followed by reinforcement learning to maximize list-wise utility and outperforming baselines on benchmarks and industrial data.
- Deep Interest Mining for Intent-Enriched Semantic IDs in Multimodal Generative Recommendation