5 papers
W2T: LoRA Weights Already Know What They Can Do
Xiaolong Han, Ferrante Neri, Zijian Jiang +4
Each LoRA checkpoint compactly stores task-specific updates in low-rank weight matrices, offering an efficient way to adapt large language models to new tasks and domains. In princ…
A Survey of Weight Space Learning: Understanding, Representation, and Generation
Xiaolong Han, Zehong Wang, Bo Zhao +8
Neural network weights are typically viewed as the end product of training, while most deep learning research focuses on data, features, and architectures. However, recent advances…
Cyberbullying Detection via Aggression-Enhanced Prompting
Aisha Saeid, Anu Sabu, Girish A. Koushik +2
Detecting cyberbullying on social media remains a critical challenge due to its subtle and varied expressions. This study investigates whether integrating aggression detection as a…
DASViT: Differentiable Architecture Search for Vision Transformer
Pengjin Wu, Ferrante Neri, Zhenhua Feng
Designing effective neural networks is a cornerstone of deep learning, and Neural Architecture Search (NAS) has emerged as a powerful tool for automating this process. Among the ex…
SiamNAS: Siamese Surrogate Model for Dominance Relation Prediction in Multi-objective Neural Architecture Search
Yuyang Zhou, Ferrante Neri, Yew-Soon Ong +1
Modern neural architecture search (NAS) is inherently multi-objective, balancing trade-offs such as accuracy, parameter count, and computational cost. This complexity makes NAS com…