2 papers
cs.IR2026
MTFM: A Scalable and Alignment-free Foundation Model for Industrial Recommendation in Meituan
Xin Song, Zhilin Guan, Ruidong Han +12
Industrial recommendation systems typically involve multiple scenarios, yet existing cross-domain (CDR) and multi-scenario (MSR) methods often require prohibitive resources and str…
cs.LG2025
Balance-aware Sequence Sampling Makes Multi-modal Learning Better
Zhi-Hao Guan
To address the modality imbalance caused by data heterogeneity, existing multi-modal learning (MML) approaches primarily focus on balancing this difference from the perspective of…