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This paper proposes GenCDSR, a generative framework for cross-domain sequential recommendation with hybrid tokenization and serial-parallel decoding, achieving improved accuracy and significantly reduced inference latency compared to state-of-the-art baselines.
Meta's In-Kernel Broadcast Optimization (IKBO) eliminates redundant user-embedding broadcast in RecSys inference via kernel-model-system co-design, delivering up to 2/3 latency reduction and ~4x speedup on H100 GPUs, and serving as the backbone for the Meta Adaptive Ranking Model.