2 papers
cs.IR2026
NSFL: A Post-Training Neuro-Symbolic Fuzzy Logic Framework for Boolean Operators in Neural Embeddings
Vladi Vexler, Ofer Idan, Gil Lederman +1
Standard dense retrievers lack a native calculus for multi-atom logical constraints. We introduce Neuro-Symbolic Fuzzy Logic (NSFL), a framework that adapts formal t-norms and t-co…
cs.LG2024
Rotation Invariant Quantization for Model Compression
Joseph Kampeas, Yury Nahshan, Hanoch Kremer +4
Post-training Neural Network (NN) model compression is an attractive approach for deploying large, memory-consuming models on devices with limited memory resources. In this study,…