3 papers
cs.CR2026
When Context Bites: Detecting RAG Poisoning via Document-Level Attention Collapse
Yingtao Ren, Ziyi Zhao, Yiwei Fu +3
Retrieval-augmented generation (RAG) is indispensable for enhancing large language models. However, RAGs are increasingly susceptible to poisoning attacks, in which adversarial doc…
cs.LG2026
iFuzz-Meta: An Interpretable Fuzzy Learning Framework Bridging Top-Down and Bottom-Up Knowledge Integration
Xiaowei Jiang, Daniel Leong, Beining Cao +5
Interpretable representation learning remains a key challenge in modern neural computation, particularly when models are expected not only to perform but also to explain their reas…
cs.LG2024
A Self-Constructing Multi-Expert Fuzzy System for High-dimensional Data Classification
Yingtao Ren, Yu-Cheng Chang, Thomas Do +2
Fuzzy Neural Networks (FNNs) are effective machine learning models for classification tasks, commonly based on the Takagi-Sugeno-Kang (TSK) fuzzy system. However, when faced with h…