Autoregressive sequential recommendation trains transformer models on tokenized user behavior via cross-entropy. The Muon optimizer projects gradient matrices onto the Stiefel manifold through Newton-Schulz (NS) orthogonalization, ensuring uniform utilization of all parameter directions. However, we identify that this...
Jin-Xin Hu, Hao Deng, Hai-Bo Xing et al.· Proceedings of the 20th ACM...· 0 citations
Modern AI systems advance through continuous iteration: a loop of proposing evolution directions, implementing code, training, and evaluation. While the latter three stages are increasingly automated, the starting point --- proposing effective evolution directions --- remains a critical bottleneck that still relies hea...
Jin-Xin Hu, Hao Deng, Hai-Bo Xing et al.· 1 citation
CMRec is proposed, a cross-country GR framework that injects cross-country supervision at the data level via dual-constrained, context-aware code-mixing that substantially improves recommendation quality in data-sparse countries while preserving performance in data-rich countries.
Yuan Gao, Hao Deng, Hai-Bo Xing et al.· 0 citations
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