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Huaxiong Wang

2 accepted papers

2026

MOAI: Module-Optimizing Architecture for Non-Interactive Secure Transformer Inference

ICLR 2026poster

Privacy concerns have been raised in Large Language Models (LLM) inference when models are deployed in Cloud Service Providers (CSP). Homomorphic encryption (HE) offers a promising solution by enabling secure inference directly over encrypted inputs. However, the high computational overhead of HE re…

Cited by 0SourcecodeScholar
2025

Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks

IJCAI 2025

To enhance the reliability and credibility of graph neural networks (GNNs) and improve the transparency of their decision logic, a new field of explainability of GNNs (XGNN) has emerged. However, two major limitations severely degrade the performance and hinder the generalizability of existing XGNN