31 citations · 116 across the 14 of their papers we have counts for
5 papers · 1 filter
On the Transferability of Adversarial Attacksagainst Neural Text Classifier
Liping Yuan, Xiaoqing Zheng, Yi Zhou +2
Deep neural networks are vulnerable to adversarial attacks, where a small perturbation to an input alters the model prediction. In many cases, malicious inputs intentionally crafte…
Unsupervised Summarization by Jointly Extracting Sentences and Keywords
Zongyi Li, Xiaoqing Zheng, Jun He
We present RepRank, an unsupervised graph-based ranking model for extractive multi-document summarization in which the similarity between words, sentences, and word-to-sentence can…
Improving Coreference Resolution by Leveraging Entity-Centric Features with Graph Neural Networks and Second-order Inference
Lu Liu, Zhenqiao Song, Xiaoqing Zheng +1
One of the major challenges in coreference resolution is how to make use of entity-level features defined over clusters of mentions rather than mention pairs. However, coreferent m…
Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble
Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh +2
Despite neural networks have achieved prominent performance on many natural language processing (NLP) tasks, they are vulnerable to adversarial examples. In this paper, we propose…
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework
Jiehang Zeng, Lu Liu, Xiaoqing Zheng
Many large-scale knowledge graphs are now available and ready to provide semantically structured information that is regarded as an important resource for question answering and de…