3 papers
cs.CL2026
RRAttention: Dynamic Block Sparse Attention via Per-Head Round-Robin Shifts for Long-Context Inference
Siran Liu, Guoxia Wang, Sa Wang +7
The quadratic complexity of attention mechanisms poses a critical bottleneck for large language models processing long contexts. While dynamic sparse attention methods offer input-…
cs.LG2025
Hierarchical LoRA MoE for Efficient CTR Model Scaling
Zhichen Zeng, Mengyue Hang, Xiaolong Liu +11
Deep models have driven significant advances in click-through rate (CTR) prediction. While vertical scaling via layer stacking improves model expressiveness, the layer-by-layer seq…
cs.IR2025
InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction
Zhichen Zeng, Xiaolong Liu, Mengyue Hang +25
Click-through rate (CTR) prediction, which predicts the probability of a user clicking an ad, is a fundamental task in recommender systems. The emergence of heterogeneous informati…