59 citations · 99 across the 11 of their papers we have counts for
11 papers
Adversarial Self-Attention for Language Understanding
Hongqiu Wu, Ruixue Ding, Hai Zhao +3
Deep neural models (e.g. Transformer) naturally learn spurious features, which create a ``shortcut'' between the labels and inputs, thus impairing the generalization and robustness…
Towards Unifying the Label Space for Aspect- and Sentence-based Sentiment Analysis
Yiming Zhang, Min Zhang, Sai Wu +1
The aspect-based sentiment analysis (ABSA) is a fine-grained task that aims to determine the sentiment polarity towards targeted aspect terms occurring in the sentence. The develop…
A Label Dependence-aware Sequence Generation Model for Multi-level Implicit Discourse Relation Recognition
Changxing Wu, Liuwen Cao, Yubin Ge +3
Implicit discourse relation recognition (IDRR) is a challenging but crucial task in discourse analysis. Most existing methods train multiple models to predict multi-level labels in…
Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability
Yifeng Xiong, Jiadong Lin, Min Zhang +2
The black-box adversarial attack has attracted impressive attention for its practical use in the field of deep learning security. Meanwhile, it is very challenging as there is no a…
Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation
Xin Liu, Baosong Yang, Dayiheng Liu +5
A well-known limitation in pretrain-finetune paradigm lies in its inflexibility caused by the one-size-fits-all vocabulary. This potentially weakens the effect when applying pretra…
Not All Attention Is All You Need
Hongqiu Wu, Hai Zhao, Min Zhang
Beyond the success story of pre-trained language models (PrLMs) in recent natural language processing, they are susceptible to over-fitting due to unusual large model size. To this…
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding
Yang Xu, Yiheng Xu, Tengchao Lv +9
Pre-training of text and layout has proved effective in a variety of visually-rich document understanding tasks due to its effective model architecture and the advantage of large-s…
Code Summarization with Structure-induced Transformer
Hongqiu Wu, Hai Zhao, Min Zhang
Code summarization (CS) is becoming a promising area in recent language understanding, which aims to generate sensible human language automatically for programming language in the…
Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization
Min Zhang, Yao Shu, Kun He
Finite-sum optimization plays an important role in the area of machine learning, and hence has triggered a surge of interest in recent years. To address this optimization problem,…
Stochastic Item Descent Method for Large Scale Equal Circle Packing Problem
Kun He, Min Zhang, Jianrong Zhou +2
Stochastic gradient descent (SGD) is a powerful method for large-scale optimization problems in the area of machine learning, especially for a finite-sum formulation with numerous…
Single versus Double Blind Reviewing at WSDM 2017
Andrew Tomkins, Min Zhang, William D. Heavlin
In this paper we study the implications for conference program committees of using single-blind reviewing, in which committee members are aware of the names and affiliations of pap…