Reproduce “Where Beam Search Loses Top-Ranked Items:First-Step Coverage in Generative Recommendation” on OpenResearch

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About this paper

Heng Yao, Hanwei Zhu

The authors reallocate beam capacity to the first token position in TIGER decoding, preserving the model and identifiers. In Sports with RQ-VAE identifiers, Front-151 raises Search Recall@10 from 0.8839 to 0.9929 at nominal budget 151. Across three domains and 77,373 users, Front-151 matches Beam-100’s ordered top ten at budgets 151 versus 301, while measured decoder latency falls 6.35–6.39%.

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