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Climber-Pilot: A Non-Myopic Generative Recommendation Model Towards Better Instruction-Following

arXiv:2602.13581v2 Announce Type: replace Abstract: Generative retrieval has emerged as a promising paradigm in recommender systems, offering superior sequence modeling capabilities over traditional dual-tower architectures. However, in large-scale industrial scenarios, such models often suffer from inherent myopia: due to single-step inference and strict latency constraints, they tend to collapse diverse user intents into locally optimal predictions, failing to capture long-horizon and...