4 papers
Learning to Rotate: Temporal and Semantic Rotary Encoding for Sequential Modeling
Hailing Cheng, Daqi Sun, Xinyu Lu
Every Transformer architecture dedicates enormous capacity to learning rich representations in semantic embedding space -- yet the rotation manifold acted upon by Rotary Positional…
Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models
Hailing Cheng, Tao Huang, Chen Zhu +1
Training large neural networks with data-parallel stochastic gradient descent allocates N GPU replicas to compute effectively identical updates -- a practice that leaves the rich s…
Isotonic Layer: A Unified Framework for Recommendation Calibration and Debiasing
Hailing Cheng, Yafang Yang, Hemeng Tao +1
Model calibration and debiasing are fundamental yet operationally expensive challenges in large-scale recommendation systems. Existing approaches treat them as separate problems re…
Beyond Interleaving: Causal Attention Reformulations for Generative Recommender Systems
Hailing Cheng
Generative Recommender Systems (GR) increasingly model user behavior as a sequence generation task by interleaving item and action tokens. While effective, this formulation introdu…