111 citations · 380 across the 48 of their papers we have counts for
8 papers · 2 filters
Temporal-aware Language Representation Learning From Crowdsourced Labels
Yang Hao, Xiao Zhai, Wenbiao Ding +1
Learning effective language representations from crowdsourced labels is crucial for many real-world machine learning tasks. A challenging aspect of this problem is that the quality…
Automatic Task Requirements Writing Evaluation via Machine Reading Comprehension
Shiting Xu, Guowei Xu, Peilei Jia +3
Task requirements (TRs) writing is an important question type in Key English Test and Preliminary English Test. A TR writing question may include multiple requirements and a high-q…
Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models
Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao +6
Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options. SC questions are widely…
Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models
Yang Hao, Hang Li, Wenbiao Ding +4
In this work, we study computational approaches to detect online dialogic instructions, which are widely used to help students understand learning materials, and build effective st…
Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining
Guowei Xu, Wenbiao Ding, Weiping Fu +2
Many real-world applications involve the use of Optical Character Recognition (OCR) engines to transform handwritten images into transcripts on which downstream Natural Language Pr…
Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence
Jian Guan, Xiaoxi Mao, Changjie Fan +3
Generating long and coherent text is an important but challenging task, particularly for open-ended language generation tasks such as story generation. Despite the success in model…
OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics
Jian Guan, Zhexin Zhang, Zhuoer Feng +5
Automatic metrics are essential for developing natural language generation (NLG) models, particularly for open-ended language generation tasks such as story generation. However, ex…
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
Haochen Liu, Wei Jin, Hamid Karimi +2
It is evident that deep text classification models trained on human data could be biased. In particular, they produce biased outcomes for texts that explicitly include identity ter…