128 citations · 718 across the 52 of their papers we have counts for
5 papers · 1 filter
Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability
Ninghao Liu, Yunsong Meng, Xia Hu +2
Recent years have witnessed an increasing number of interpretation methods being developed for improving transparency of NLP models. Meanwhile, researchers also try to answer the q…
Explainable Recommender Systems via Resolving Learning Representations
Ninghao Liu, Yong Ge, Li Li +3
Recommender systems play a fundamental role in web applications in filtering massive information and matching user interests. While many efforts have been devoted to developing mor…
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks
Ruixiang Tang, Mengnan Du, Ninghao Liu +2
With the widespread use of deep neural networks (DNNs) in high-stake applications, the security problem of the DNN models has received extensive attention. In this paper, we invest…
Adversarial Attacks and Defenses: An Interpretation Perspective
Ninghao Liu, Mengnan Du, Ruocheng Guo +2
Despite the recent advances in a wide spectrum of applications, machine learning models, especially deep neural networks, have been shown to be vulnerable to adversarial attacks. A…
Learning to Hash with Graph Neural Networks for Recommender Systems
Qiaoyu Tan, Ninghao Liu, Xing Zhao +3
Graph representation learning has attracted much attention in supporting high quality candidate search at scale. Despite its effectiveness in learning embedding vectors for objects…