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cs.IR2026
Beyond Dense Connectivity: Explicit Sparsity for Scalable Recommendation
Yantao Yu, Sen Qiao, Lei Shen +2
Recent progress in scaling large models has motivated recommender systems to increase model depth and capacity to better leverage massive behavioral data. However, recommendation i…
cs.IR2026
SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress
Yang Yu, Lei Kou, Huaikuan Yi +6
With the rapid evolution of Large Language Models (LLMs), generative recommendation is gradually reshaping the paradigm of recommender systems. However, most existing methods remai…
cs.IR2025
Scaling Transformers for Discriminative Recommendation via Generative Pretraining
Chunqi Wang, Bingchao Wu, Zheng Chen +3
Discriminative recommendation tasks, such as CTR (click-through rate) and CVR (conversion rate) prediction, play critical roles in the ranking stage of large-scale industrial recom…