48 citations · 142 across the 9 of their papers we have counts for
9 papers
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information
Zijun Sun, Xiaoya Li, Xiaofei Sun +6
Recent pretraining models in Chinese neglect two important aspects specific to the Chinese language: glyph and pinyin, which carry significant syntax and semantic information for l…
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…
Summarize, Outline, and Elaborate: Long-Text Generation via Hierarchical Supervision from Extractive Summaries
Xiaofei Sun, Zijun Sun, Yuxian Meng +2
The difficulty of generating coherent long texts lies in the fact that existing models overwhelmingly focus on predicting local words, and cannot make high level plans on what to g…
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…
Entity-Relation Extraction as Multi-Turn Question Answering
Xiaoya Li, Fan Yin, Zijun Sun +6
In this paper, we propose a new paradigm for the task of entity-relation extraction. We cast the task as a multi-turn question answering problem, i.e., the extraction of entities a…
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…