All in One: Multi-Task Prompting for Graph Neural Networks
统一 graph/edge/node-level 的 graph prompt
Empirical
Transformers need glasses! Information Over-Squashing in Language Tasks
LLM Representational Collapse
Data Augmentation as Free Lunch: Exploring the Test-Time Augmentation for Sequential Recommendation
TTA, Test-Time Augmentation
CPT: Efficient Deep Neural Network Training via Cyclic Precision
CPT, 类似 CosineAnnealingWarmRestarts 的 Precision 循环机制
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients
Q-GaLore, 对 GaLore 进一步施加低精度量化
SWALP: Stochastic Weight Averaging in Low-Precision Training
SWALP, 通过 SWA 稳定低精度训练
Scaling Laws for Online Advertisement Retrieval
快手, 广告场景下的 Scaling Laws
EMR-MERGING: Tuning-Free High-Performance Model Merging
EMR-MERGING, 多任务权重合并技术
QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou
QARM, 多模态推荐对齐与量化
Language Representations Can be What Recommenders Need: Findings and Potentials
Next-token embedding 之于协同过滤