25 citations · 53 across the 4 of their papers we have counts for
6 papers
Self-Explaining Structures Improve NLP Models
Zijun Sun, Chun Fan, Qinghong Han +4
Existing approaches to explaining deep learning models in NLP usually suffer from two major drawbacks: (1) the main model and the explaining model are decoupled: an additional prob…
Neural Semi-supervised Learning for Text Classification Under Large-Scale Pretraining
Zijun Sun, Chun Fan, Xiaofei Sun +3
The goal of semi-supervised learning is to utilize the unlabeled, in-domain dataset U to improve models trained on the labeled dataset D. Under the context of large-scale language-…
Pair the Dots: Jointly Examining Training History and Test Stimuli for Model Interpretability
Yuxian Meng, Chun Fan, Zijun Sun +3
Any prediction from a model is made by a combination of learning history and test stimuli. This provides significant insights for improving model interpretability: {\it because of…
Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs
Yuxian Meng, Xiangyuan Ren, Zijun Sun +4
In this paper, we investigate the problem of training neural machine translation (NMT) systems with a dataset of more than 40 billion bilingual sentence pairs, which is larger than…
Query-Based Named Entity Recognition
Yuxian Meng, Xiaoya Li, Zijun Sun +1
In this paper, we propose a new strategy for the task of named entity recognition (NER). We cast the task as a query-based machine reading comprehension task: e.g., the task of ext…
IcoRating: A Deep-Learning System for Scam ICO Identification
Shuqing Bian, Zhenpeng Deng, Fei Li +9
Cryptocurrencies (or digital tokens, digital currencies, e.g., BTC, ETH, XRP, NEO) have been rapidly gaining ground in use, value, and understanding among the public, bringing asto…