4 citations · 14 across the 9 of their papers we have counts for
9 papers
ADELT: Transpilation Between Deep Learning Frameworks
Linyuan Gong, Jiayi Wang, Alvin Cheung
We propose the Adversarial DEep Learning Transpiler (ADELT), a novel approach to source-to-source transpilation between deep learning frameworks. ADELT uniquely decouples code skel…
Rethinking Textual Adversarial Defense for Pre-trained Language Models
Jiayi Wang, Rongzhou Bao, Zhuosheng Zhang +1
Although pre-trained language models (PrLMs) have achieved significant success, recent studies demonstrate that PrLMs are vulnerable to adversarial attacks. By generating adversari…
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model
Jiayi Wang, Rongzhou Bao, Zhuosheng Zhang +1
Recently, the problem of robustness of pre-trained language models (PrLMs) has received increasing research interest. Latest studies on adversarial attacks achieve high attack succ…
Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation
Ke Wang, Yangbin Shi, Jiayi Wang +3
Quality Estimation (QE) plays an essential role in applications of Machine Translation (MT). Traditionally, a QE system accepts the original source text and translation from a blac…
Defending Pre-trained Language Models from Adversarial Word Substitutions Without Performance Sacrifice
Rongzhou Bao, Jiayi Wang, Hai Zhao
Pre-trained contextualized language models (PrLMs) have led to strong performance gains in downstream natural language understanding tasks. However, PrLMs can still be easily foole…
Enhancing Pre-trained Language Model with Lexical Simplification
Rongzhou Bao, Jiayi Wang, Zhuosheng Zhang +1
For both human readers and pre-trained language models (PrLMs), lexical diversity may lead to confusion and inaccuracy when understanding the underlying semantic meanings of given…
Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing
Jiayi Wang, Ke Wang, Niyu Ge +3
With the advent of neural machine translation, there has been a marked shift towards leveraging and consuming the machine translation results. However, the gap between machine tran…
Neural Zero-Inflated Quality Estimation Model For Automatic Speech Recognition System
Kai Fan, Jiayi Wang, Bo Li +4
The performances of automatic speech recognition (ASR) systems are usually evaluated by the metric word error rate (WER) when the manually transcribed data are provided, which are,…
"Bilingual Expert" Can Find Translation Errors
Kai Fan, Jiayi Wang, Bo Li +3
Recent advances in statistical machine translation via the adoption of neural sequence-to-sequence models empower the end-to-end system to achieve state-of-the-art in many WMT benc…