Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval (2024.emnlp-industry)
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Zhirui Kuai, Zuxu Chen, Huimu Wang, Mingming Li, Dadong Miao, Wang Binbin, Xusong Chen, Li Kuang, Yuxing Han, Jiaxing Wang, Guoyu Tang, Lin Liu, Songlin Wang, Jingwei Zhuo
| Challenge: | Generative retrieval (GR) is a transformative paradigm in search and recommender systems . however, data sparsity and long-tailed distribution hinder the full utilization of GR . |
| Approach: | They propose a method to reduce the "Hourglass" phenomenon in RQ-SID where codebook tokens become overly concentrated. |
| Outcome: | The proposed methods improve retrieval efficiency and generalization capabilities. |
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