Topology-Aware Tokenization (TopoTok) Improves Generative Recommendation Accuracy
A new preprint introduces TopoTok, a tokenization framework designed to preserve item relational structure during quantization in generative recommendation systems. By employing a multi-level distillation approach—addressing global, local, and item-level relationships—TopoTok reduces topology distortion that can hinder recommendation accuracy. Experiments on three benchmark datasets show that TopoTok outperforms existing tokenizers, with improvements of up to 9.42% in Recall@5.
Why it matters: This work offers a notable advance in generative recommendation by addressing topology distortion, a key limitation in current tokenization methods, and demonstrates substantial accuracy gains.
Full story at: arXiv Information Retrieval ↗