PRQ-KMeans: Projection Residual Quantization for Semantic ID Tokenization

arXiv:2608.24207 · cs.LG · Submitted 2026-08-25 · Read on arXiv

cs.LG

Submitted: 2026-08-25

Updated: 2026-09-03

Terminology

• Benchmark — 22× in this paper · explained in 2 episodes
• Quantization — 19× in this paper · explained in 12 episodes
• Embeddings — 11× in this paper · explained in 2 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Generative Recommendation — 8× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Tokenization — 6× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Reasoning — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Residualization — 1× in this paper · explained in 2 episodes
• Self-Distillation — 1× in this paper · explained in 7 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
• OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework
• Quantizing Intent: Cross-Domain Semantic IDs from Organic Activity for Industrial Ranking
• OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment
• Differentiable Semantic ID for Generative Recommendation
• End-to-End Semantic ID Generation for Generative Advertisement Recommendation
• KuaiSearch: An E-Commerce Search Dataset with Authentic Queries and Product Texts for Recall, Ranking, and Relevance
• Rethinking Generative Recommender Tokenizer: Recsys-Native Encoding and Semantic Quantization Beyond LLMs
• Generative Recommender with End-to-End Learnable Item Tokenization
• Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models
• LLaDA-Rec: Discrete Diffusion for Parallel Semantic ID Generation in Generative Recommendation
• RQ-GMM: Residual Quantized Gaussian Mixture Model for Multimodal Semantic Discretization in CTR Prediction
• R3-VAE: Reference Vector-Guided Rating Residual Quantization VAE for Generative Recommendation
• Unleash the Potential of Long Semantic IDs for Generative Recommendation
• QARM V2: Quantitative Alignment Multi-Modal Recommendation for Reasoning User Sequence Modeling
• How Reliable Are Semantic-ID Tokenizer Comparisons in Generative Recommendation?
• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

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