111 citations · 380 across the 48 of their papers we have counts for
49 papers
GUIOdyssey: A Comprehensive Dataset for Cross-App GUI Navigation on Mobile Devices
Quanfeng Lu, Wenqi Shao, Zitao Liu +7
Autonomous Graphical User Interface (GUI) navigation agents can enhance user experience in communication, entertainment, and productivity by streamlining workflows and reducing man…
A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models
Hengyuan Zhang, Zitao Liu, Chenming Shang +2
Knowledge tracing (KT) plays a crucial role in predicting students' future performance by analyzing their historical learning processes. Deep neural networks (DNNs) have shown grea…
Improving Low-Resource Knowledge Tracing Tasks by Supervised Pre-training and Importance Mechanism Fine-tuning
Hengyuan Zhang, Zitao Liu, Shuyan Huang +3
Knowledge tracing (KT) aims to estimate student's knowledge mastery based on their historical interactions. Recently, the deep learning based KT (DLKT) approaches have achieved imp…
Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations
Jiahao Chen, Zitao Liu, Shuyan Huang +2
Knowledge tracing (KT) is a crucial technique to predict students' future performance by observing their historical learning processes. Due to the powerful representation ability o…
simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing
Zitao Liu, Qiongqiong Liu, Jiahao Chen +2
Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems. Recently, many works pres…
Fairly Adaptive Negative Sampling for Recommendations
Xiao Chen, Wenqi Fan, Jingfan Chen +4
Pairwise learning strategies are prevalent for optimizing recommendation models on implicit feedback data, which usually learns user preference by discriminating between positive (…
Enhancing Deep Knowledge Tracing with Auxiliary Tasks
Zitao Liu, Qiongqiong Liu, Jiahao Chen +4
Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems. Recent studies have appli…
Probabilistic Categorical Adversarial Attack & Adversarial Training
Han Xu, Pengfei He, Jie Ren +4
The existence of adversarial examples brings huge concern for people to apply Deep Neural Networks (DNNs) in safety-critical tasks. However, how to generate adversarial examples wi…
Wide & Deep Learning for Judging Student Performance in Online One-on-one Math Classes
Jiahao Chen, Zitao Liu, Weiqi Luo
In this paper, we investigate the opportunities of automating the judgment process in online one-on-one math classes. We build a Wide & Deep framework to learn fine-grained predict…
A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning
Shuyan Huang, Qiongqiong Liu, Jiahao Chen +3
We propose a simple but effective method to recommend exercises with high quality and diversity for students. Our method is made up of three key components: (1) candidate generatio…
SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners
Qiongqiong Liu, Yaying Huang, Zitao Liu +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…
DialogID: A Dialogic Instruction Dataset for Improving Teaching Effectiveness in Online Environments
Jiahao Chen, Shuyan Huang, Zitao Liu +1
Online dialogic instructions are a set of pedagogical instructions used in real-world online educational contexts to motivate students, help understand learning materials, and buil…
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models
Zitao Liu, Qiongqiong Liu, Jiahao Chen +3
Knowledge tracing (KT) is the task of using students' historical learning interaction data to model their knowledge mastery over time so as to make predictions on their future inte…
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations
Hang Li, Yu Kang, Tianqiao Liu +2
Existing audio-language task-specific predictive approaches focus on building complicated late-fusion mechanisms. However, these models are facing challenges of overfitting with li…
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…
A Multimodal Machine Learning Framework for Teacher Vocal Delivery Evaluation
Hang Li, Yu Kang, Yang Hao +3
The quality of vocal delivery is one of the key indicators for evaluating teacher enthusiasm, which has been widely accepted to be connected to the overall course qualities. Howeve…
An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms
Jiahao Chen, Hang Li, Wenbiao Ding +1
In this paper, we propose a simple yet effective solution to build practical teacher recommender systems for online one-on-one classes. Our system consists of (1) a pseudo matching…
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…
Towards the Memorization Effect of Neural Networks in Adversarial Training
Han Xu, Xiaorui Liu, Wentao Wang +5
Recent studies suggest that ``memorization'' is one important factor for overparameterized deep neural networks (DNNs) to achieve optimal performance. Specifically, the perfectly f…
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…