Krishna Kandi

Adaptive Weighted Loss for Sequential Recommendations on Sparse Domains

2025 · arXiv (Cornell University)

The effectiveness of single-model sequential recommendation architectures, while scalable, is often limited when catering to "power users" in sparse or niche domains. Our previous research, PinnerFormerLite, addressed this by using a fixed weighted loss to …