Author

Lian-Jie Li

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Preprint Aug 2026

History-Conditioned Joint-Prefix Alignment for Generative Recommendation

Prefix Alignment with Temporal History (PATH), which aggregates transition statistics from the training corpus over recent interactions with exponential decay to construct history-conditioned two-token prefix targets, is proposed, showing consistent improvements in recommendation performance and higher full-SID surviva...

Hong-Liang Sun, Lian-Jie Li, Bolin Zhang et al. · 1 citation

#artificial intelligence Preprint Aug 2026

TAAL: Mitigating Early Beam Pruning in Generative Recommendation via Temporal Autoregressive Alignment

Temporal Autoregressive Alignment (TAAL) is proposed, which improves NDCG@10 over the standard baseline by 39.5%, and aligns the early-prefix distribution with a forward KL objective during training and during inference, it calibrates candidate scores with pointwise mutual information (PMI) to reduce the influence of g...

Lian-Jie Li, Zhi-Ying Tu, Dianhui Chu et al. · 0 citations