Researchers proposed Sharp Mode Connectivity (SMC), a sharpness-aware reformulation of mode connectivity that enforces low loss across the entire neighborhood of a weight-space interpolation curve rat…
Researchers at KAU QuantumAILab propose TESLA, a learnable sinusoidal activation that solves the parity problem for binary vectors of length 32 with 100,000 training samples (0.002% of the input space…
Researchers present Subtoken Vision Transformer (SubViT), a selective image tokenization method that improves fine-grained visual recognition by representing discriminative patches with multiple subto…
Researchers propose LEAP, a training curriculum for Vision Transformer feature-based knowledge distillation that uses the teacher's intermediate feature maps as progressively difficult targets. LEAP a…