Search papers, labs, and topics across Lattice.
College of Computer Science and Software Engineering, Shenzhen University
5
0
9
0
Overcome data sparsity in sequential recommendation with a new framework that learns fine-grained user preferences from diverse behaviors, leading to state-of-the-art performance.
LVLMs can run 2.3x faster with only a 2% accuracy drop, thanks to a new pruning method that understands which visual tokens are most relevant to the text.
Achieve superior remote sensing performance at a fraction of the cost by intelligently sampling high-resolution imagery based on global context and fine-grained patch importance.
PReD leaps ahead by creating the first foundation model to close the loop on perception, recognition, and decision-making for electromagnetic signals.
By focusing on activation-space tail eigenvectors, Astra unlocks better fine-tuning with fewer parameters, even beating full fine-tuning in some cases.
