3 papers
cs.DC2026
DepTGL: A Parallel Framework for Memory-based TGNN Training with Adaptive Temporal Data Dependency Management
Linfang Chen, Zhen Song, Lei Liu +6
Memory-based Temporal Graph Neural Networks (M-TGNNs) maintain recursively updated node states to capture fine-grained temporal interactions. However, existing distributed framewor…
cs.LG2026
GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer Selection
Kai Yao, Zhenghan Song, Kaixin Wu +5
Parameter-Efficient Fine-Tuning (PEFT) has become a key strategy for adapting large language models, with recent advances in sparse tuning reducing overhead by selectively updating…
cs.LG2026
FEAT: A Linear-Complexity Foundation Model for Extremely Large Structured Data
Zhenghang Song, Tang Qian, Lu Chen +7
Structured data is widely used in domains such as healthcare, finance, and scientific data management. Recent studies on structured data foundation models (SFMs) aim to support dat…