Task-Feature Specialization explains weight disentanglement in task arithmetic and leads to orthogonality, which OrthoReg enforces to enhance performance of model composition methods.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
FSNet detects unknown invisible watermarks via adaptive frequency gating and multi-spectral attention on the UniFreq-100K dataset, claiming superior zero-shot performance.
citing papers explorer
-
Understanding and Enforcing Weight Disentanglement in Task Arithmetic
Task-Feature Specialization explains weight disentanglement in task arithmetic and leads to orthogonality, which OrthoReg enforces to enhance performance of model composition methods.
-
AWPD: Frequency Shield Network for Agnostic Watermark Presence Detection
FSNet detects unknown invisible watermarks via adaptive frequency gating and multi-spectral attention on the UniFreq-100K dataset, claiming superior zero-shot performance.