2 papers
cs.CV2026
Low-Rank Ternary Adaptation for Fine-Tuning Transformers
Alexandru-Dragos Manolache, Yunqiang Li, Jan van Gemert
Ternary transformers offer extreme memory and compute efficiency, but existing low-bit LoRA-based methods cannot directly fine-tune ternary weights. Current approaches either requi…
cs.SI2026
Physics-Informed Neural Network with Adaptive Clustering Learning Mechanism for Information Popularity Prediction
Guangyin Jin, Xiaohan Ni, Yanjie Song +4
With society entering the Internet era, the volume and speed of data and information have been increasing. Predicting the popularity of information cascades can help with high-valu…