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cs.LG2026
Cut Binary Cross Entropy: Efficient Large-Vocabulary Loss and Gradient Kernels for Sequential Recommendation
Yaoyiran Li, Haowen Ning, Mohamed Hammad
Industrial sequential recommender systems operate over massive item catalogs (e.g., 10^5--10^7 items). Multi-label recommendation models are trained with Binary Cross-Entropy (BCE)…
cs.LG2024★ 6 cited
Liger Kernel: Efficient Triton Kernels for LLM Training
Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli +7
Training Large Language Models (LLMs) efficiently at scale presents a formidable challenge, driven by their ever-increasing computational demands and the need for enhanced performa…