Search Results for author: Zitao Liu

Found 63 papers, 33 papers with code

MLPST: MLP is All You Need for Spatio-Temporal Prediction

no code implementations23 Sep 2023 Zijian Zhang, Ze Huang, Zhiwei Hu, Xiangyu Zhao, Wanyu Wang, Zitao Liu, Junbo Zhang, S. Joe Qin, Hongwei Zhao

To accomplish the above goals, we propose an intuitive and novel framework, MLPST, a pure multi-layer perceptron architecture for traffic prediction.

Traffic Prediction

Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting

1 code implementation20 Sep 2023 Qian Ma, Zijian Zhang, Xiangyu Zhao, Haoliang Li, Hongwei Zhao, Yiqi Wang, Zitao Liu, Wanyu Wang

Then, we generate representative and common spatio-temporal patterns as global nodes to reflect a global dependency between sensors and provide auxiliary information for spatio-temporal dependency learning.

PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction

no code implementations18 Sep 2023 Zijian Zhang, Xiangyu Zhao, Qidong Liu, Chunxu Zhang, Qian Ma, Wanyu Wang, Hongwei Zhao, Yiqi Wang, Zitao Liu

We devise a spatio-temporal transformer and a parameter-sharing training scheme to address the common knowledge among different spatio-temporal attributes.

Fairly Adaptive Negative Sampling for Recommendations

no code implementations16 Feb 2023 Xiao Chen, Wenqi Fan, Jingfan Chen, Haochen Liu, Zitao Liu, Zhaoxiang Zhang, Qing Li

Pairwise learning strategies are prevalent for optimizing recommendation models on implicit feedback data, which usually learns user preference by discriminating between positive (i. e., clicked by a user) and negative items (i. e., obtained by negative sampling).


Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations

no code implementations14 Feb 2023 Jiahao Chen, Zitao Liu, Shuyan Huang, Qiongqiong Liu, Weiqi Luo

The results demonstrate that our approach is superior on the KT prediction task, and it outperforms a wide range of deep learning based KT models in terms of prediction accuracy with better model interpretability.

Knowledge Tracing

simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing

1 code implementation14 Feb 2023 Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Weiqi Luo

Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems.

Knowledge Tracing

Enhancing Deep Knowledge Tracing with Auxiliary Tasks

1 code implementation14 Feb 2023 Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Boyu Gao, Weiqi Luo, Jian Weng

In this paper, we proposed \emph{AT-DKT} to improve the prediction performance of the original deep knowledge tracing model with two auxiliary learning tasks, i. e., \emph{question tagging (QT) prediction task} and \emph{individualized prior knowledge (IK) prediction task}.

Auxiliary Learning Knowledge Tracing

Probabilistic Categorical Adversarial Attack & Adversarial Training

no code implementations17 Oct 2022 Pengfei He, Han Xu, Jie Ren, Yuxuan Wan, Zitao Liu, Jiliang Tang

To tackle this problem, we propose Probabilistic Categorical Adversarial Attack (PCAA), which transfers the discrete optimization problem to a continuous problem that can be solved efficiently by Projected Gradient Descent.

Adversarial Attack

Wide & Deep Learning for Judging Student Performance in Online One-on-one Math Classes

1 code implementation13 Jul 2022 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.

SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners

1 code implementation24 Jun 2022 Qiongqiong Liu, Yaying Huang, Zitao Liu, Shuyan Huang, Jiahao Chen, Xiangyu Zhao, Guimin Lin, Yuyu Zhou, Weiqi Luo

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.

Sentence Completion

DialogID: A Dialogic Instruction Dataset for Improving Teaching Effectiveness in Online Environments

1 code implementation24 Jun 2022 Jiahao Chen, Shuyan Huang, Zitao Liu, Weiqi Luo

In spite of the popularity and advantages of online learning, the education technology and educational data mining communities still suffer from the lack of large-scale, high-quality, and well-annotated teaching instruction datasets to study computational approaches to automatically detect online dialogic instructions and further improve the online teaching effectiveness.

A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning

no code implementations23 Jun 2022 Shuyan Huang, Qiongqiong Liu, Jiahao Chen, Xiangen Hu, Zitao Liu, Weiqi Luo

We propose a simple but effective method to recommend exercises with high quality and diversity for students.

pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models

1 code implementation23 Jun 2022 Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Jiliang Tang, Weiqi Luo

However, the success behind deep learning based knowledge tracing (DLKT) approaches is still left somewhat unknown and proper measurement and analysis of these DLKT approaches remain a challenge.

Knowledge Tracing

A Knowledge-Based Decision Support System for In Vitro Fertilization Treatment

no code implementations27 Jan 2022 Xizhe Wang, Ning Zhang, Jia Wang, Jing Ni, Xinzi Sun, John Zhang, Zitao Liu, Yu Cao, Benyuan Liu

To improve the IVF success rate, we propose a knowledge-based decision support system that can provide medical advice on the treatment protocol and medication adjustment for each patient visit during IVF treatment cycle.


Graph Neural Networks with Adaptive Residual

1 code implementation NeurIPS 2021 Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang

Graph neural networks (GNNs) have shown the power in graph representation learning for numerous tasks.

Graph Representation Learning

Automatic Task Requirements Writing Evaluation via Machine Reading Comprehension

1 code implementation15 Jul 2021 Shiting Xu, Guowei Xu, Peilei Jia, Wenbiao Ding, Zhongqin Wu, Zitao Liu

A TR writing question may include multiple requirements and a high-quality essay must respond to each requirement thoroughly and accurately.

Machine Reading Comprehension

A Multimodal Machine Learning Framework for Teacher Vocal Delivery Evaluation

1 code implementation15 Jul 2021 Hang Li, Yu Kang, Yang Hao, Wenbiao Ding, Zhongqin Wu, Zitao Liu

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.

BIG-bench Machine Learning

Temporal-aware Language Representation Learning From Crowdsourced Labels

1 code implementation ACL (RepL4NLP) 2021 Yang Hao, Xiao Zhai, Wenbiao Ding, Zitao Liu

A challenging aspect of this problem is that the quality of crowdsourced labels suffer high intra- and inter-observer variability.

Representation Learning

Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models

1 code implementation15 Jul 2021 Yang Hao, Hang Li, Wenbiao Ding, Zhongqin Wu, Jiliang Tang, Rose Luckin, Zitao Liu

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 study habits.

Multi-Task Learning

Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models

1 code implementation15 Jul 2021 Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao, Qiang Fang, Wenbiao Ding, Zhongqin Wu, Feng Xia, Jiliang Tang, Zitao Liu

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.

Sentence Completion

An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms

no code implementations15 Jul 2021 Jiahao Chen, Hang Li, Wenbiao Ding, Zitao Liu

In this paper, we propose a simple yet effective solution to build practical teacher recommender systems for online one-on-one classes.

Recommendation Systems

Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining

1 code implementation15 Jul 2021 Guowei Xu, Wenbiao Ding, Weiping Fu, Zhongqin Wu, Zitao Liu

Despite that pre-trained models achieve state-of-the-art performance in many NLP benchmarks, we prove that they are not robust to noisy texts generated by real OCR engines.

Optical Character Recognition Optical Character Recognition (OCR) +2

Towards the Memorization Effect of Neural Networks in Adversarial Training

no code implementations9 Jun 2021 Han Xu, Xiaorui Liu, Wentao Wang, Wenbiao Ding, Zhongqin Wu, Zitao Liu, Anil Jain, Jiliang Tang

In this work, we study the effect of memorization in adversarial trained DNNs and disclose two important findings: (a) Memorizing atypical samples is only effective to improve DNN's accuracy on clean atypical samples, but hardly improve their adversarial robustness and (b) Memorizing certain atypical samples will even hurt the DNN's performance on typical samples.

Adversarial Robustness Memorization

Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence

1 code implementation ACL 2021 Jian Guan, Xiaoxi Mao, Changjie Fan, Zitao Liu, Wenbiao Ding, Minlie Huang

Generating long and coherent text is an important but challenging task, particularly for open-ended language generation tasks such as story generation.

Semantic Similarity Semantic Textual Similarity +1

OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics

1 code implementation ACL 2021 Jian Guan, Zhexin Zhang, Zhuoer Feng, Zitao Liu, Wenbiao Ding, Xiaoxi Mao, Changjie Fan, Minlie Huang

Automatic metrics are essential for developing natural language generation (NLG) models, particularly for open-ended language generation tasks such as story generation.

Story Generation

The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification

no code implementations Findings (ACL) 2021 Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang

The results show that the text classification models trained under our proposed framework outperform traditional models significantly in terms of fairness, and also slightly in terms of classification performance.

Fairness General Classification +2

COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction

1 code implementation CVPR 2021 Yijie Lin, Yuanbiao Gou, Zitao Liu, Boyun Li, Jiancheng Lv, Xi Peng

In this paper, we study two challenging problems in incomplete multi-view clustering analysis, namely, i) how to learn an informative and consistent representation among different views without the help of labels and ii) how to recover the missing views from data.

Clustering Contrastive Learning +2

Partially View-aligned Representation Learning with Noise-robust Contrastive Loss

1 code implementation CVPR 2021 Mouxing Yang, Yunfan Li, Zhenyu Huang, Zitao Liu, Peng Hu, Xi Peng

To solve such a less-touched problem without the help of labels, we propose simultaneously learning representation and aligning data using a noise-robust contrastive loss.

Clustering Contrastive Learning +2

AdvExpander: Generating Natural Language Adversarial Examples by Expanding Text

no code implementations18 Dec 2020 Zhihong Shao, Zitao Liu, Jiyong Zhang, Zhongqin Wu, Minlie Huang

In this paper, we present AdvExpander, a method that crafts new adversarial examples by expanding text, which is complementary to previous substitution-based methods.

Text Matching

CLEARER: Multi-Scale Neural Architecture Search for Image Restoration

1 code implementation NeurIPS 2020 Yuanbiao Gou, Boyun Li, Zitao Liu, Songfan Yang, Xi Peng

Different from the existing labor-intensive handcrafted architecture design paradigms, we present a novel method, termed as multi-sCaLe nEural ARchitecture sEarch for image Restoration (CLEARER), which is a specifically designed neural architecture search (NAS) for image restoration.

Image Denoising Image Restoration +2

Node Similarity Preserving Graph Convolutional Networks

1 code implementation19 Nov 2020 Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang

Specifically, to balance information from graph structure and node features, we propose a feature similarity preserving aggregation which adaptively integrates graph structure and node features.

Graph Representation Learning Self-Supervised Learning

Personalized Multimodal Feedback Generation in Education

no code implementations COLING 2020 Haochen Liu, Zitao Liu, Zhongqin Wu, Jiliang Tang

The automatic evaluation for school assignments is an important application of AI in the education field.

Text Generation

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning

1 code implementation EMNLP 2020 Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu, Jiliang Tang

Extensive experiments on two real-world conversation datasets show that our framework significantly reduces gender bias in dialogue models while maintaining the response quality.

Dialogue Generation

Representation Learning from Limited Educational Data with Crowdsourced Labels

1 code implementation23 Sep 2020 Wentao Wang, Guowei Xu, Wenbiao Ding, Gale Yan Huang, Guoliang Li, Jiliang Tang, Zitao Liu

Extensive experiments conducted on three real-world data sets demonstrate the superiority of our framework on learning representations from limited data with crowdsourced labels, comparing with various state-of-the-art baselines.

Face Recognition Machine Translation +1

Contrastive Clustering

1 code implementation21 Sep 2020 Yunfan Li, Peng Hu, Zitao Liu, Dezhong Peng, Joey Tianyi Zhou, Xi Peng

In this paper, we propose a one-stage online clustering method called Contrastive Clustering (CC) which explicitly performs the instance- and cluster-level contrastive learning.

Ranked #3 on Image Clustering on STL-10 (using extra training data)

Clustering Contrastive Learning +1

Interactive Knowledge Distillation

no code implementations3 Jul 2020 Shipeng Fu, Zhen Li, Jun Xu, Ming-Ming Cheng, Zitao Liu, Xiaomin Yang

Knowledge distillation is a standard teacher-student learning framework to train a light-weight student network under the guidance of a well-trained large teacher network.

Image Classification Knowledge Distillation

Automatic Dialogic Instruction Detection for K-12 Online One-on-one Classes

no code implementations16 May 2020 Shiting Xu, Wenbiao Ding, Zitao Liu

Online one-on-one class is created for highly interactive and immersive learning experience.

Siamese Neural Networks for Class Activity Detection

no code implementations15 May 2020 Hang Li, Zhiwei Wang, Jiliang Tang, Wenbiao Ding, Zitao Liu

Classroom activity detection (CAD) aims at accurately recognizing speaker roles (either teacher or student) in classrooms.

Action Detection Activity Detection

Synchronous Bidirectional Learning for Multilingual Lip Reading

1 code implementation8 May 2020 Mingshuang Luo, Shuang Yang, Xilin Chen, Zitao Liu, Shiguang Shan

Based on this idea, we try to explore the synergized learning of multilingual lip reading in this paper, and further propose a synchronous bidirectional learning (SBL) framework for effective synergy of multilingual lip reading.

Lip Reading

Learning Goal-oriented Dialogue Policy with Opposite Agent Awareness

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Zheng Zhang, Lizi Liao, Xiaoyan Zhu, Tat-Seng Chua, Zitao Liu, Yan Huang, Minlie Huang

Most existing approaches for goal-oriented dialogue policy learning used reinforcement learning, which focuses on the target agent policy and simply treat the opposite agent policy as part of the environment.

Decision Making

Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach

no code implementations21 Mar 2020 Hang Li, Wenbiao Ding, Zitao Liu

We conduct a wide range of offline and online experiments to demonstrate the effectiveness of our approach.

BIG-bench Machine Learning

NeuCrowd: Neural Sampling Network for Representation Learning with Crowdsourced Labels

2 code implementations21 Mar 2020 Yang Hao, Wenbiao Ding, Zitao Liu

Representation learning approaches require a massive amount of discriminative training data, which is unavailable in many scenarios, such as healthcare, smart city, education, etc.

Representation Learning

Graduate Employment Prediction with Bias

no code implementations27 Dec 2019 Teng Guo, Feng Xia, Shihao Zhen, Xiaomei Bai, Dongyu Zhang, Zitao Liu, Jiliang Tang

The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide.

Learning Multi-level Dependencies for Robust Word Recognition

2 code implementations22 Nov 2019 Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu

Robust language processing systems are becoming increasingly important given the recent awareness of dangerous situations where brittle machine learning models can be easily broken with the presence of noises.

Multimodal Learning For Classroom Activity Detection

no code implementations22 Oct 2019 Hang Li, Yu Kang, Wenbiao Ding, Song Yang, Songfan Yang, Gale Yan Huang, Zitao Liu

The experimental results demonstrate the benefits of our approach on learning attention based neural network from classroom data with different modalities, and show our approach is able to outperform state-of-the-art baselines in terms of various evaluation metrics.

Action Detection Activity Detection

Does Gender Matter? Towards Fairness in Dialogue Systems

1 code implementation COLING 2020 Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu, Jiliang Tang

In particular, we construct a benchmark dataset and propose quantitative measures to understand fairness in dialogue models.


Automatic Short Answer Grading via Multiway Attention Networks

no code implementations23 Sep 2019 Tiaoqiao Liu, Wenbiao Ding, Zhiwei Wang, Jiliang Tang, Gale Yan Huang, Zitao Liu

Automatic short answer grading (ASAG), which autonomously score student answers according to reference answers, provides a cost-effective and consistent approach to teaching professionals and can reduce their monotonous and tedious grading workloads.

Say What I Want: Towards the Dark Side of Neural Dialogue Models

no code implementations13 Sep 2019 Haochen Liu, Tyler Derr, Zitao Liu, Jiliang Tang

Neural dialogue models have been widely adopted in various chatbot applications because of their good performance in simulating and generalizing human conversations.

Chatbot Reinforcement Learning (RL)

Deep Knowledge Tracing with Side Information

no code implementations1 Sep 2019 Zhiwei Wang, Xiaoqin Feng, Jiliang Tang, Gale Yan Huang, Zitao Liu

Monitoring student knowledge states or skill acquisition levels known as knowledge tracing, is a fundamental part of intelligent tutoring systems.

Knowledge Tracing

A Multimodal Alerting System for Online Class Quality Assurance

no code implementations1 Sep 2019 Jiahao Chen, Hang Li, Wenxin Wang, Wenbiao Ding, Gale Yan Huang, Zitao Liu

To warn the unqualified instructors and ensure the overall education quality, we build a monitoring and alerting system by utilizing multimodal information from the online environment.

Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education

no code implementations1 Aug 2019 Wenbiao Ding, Guowei Xu, Tianqiao Liu, Weiping Fu, Yujia Song, Chaoyou Guo, Cong Kong, Songfan Yang, Gale Yan Huang, Zitao Liu

In our offline experiments, we show that Dolphin improves both phonological fluency and semantic relevance evaluation performance when compared to state-of-the-art baselines on real-world educational data sets.

Recommender Systems with Heterogeneous Side Information

1 code implementation18 Jul 2019 Tianqiao Liu, Zhiwei Wang, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu

In modern recommender systems, both users and items are associated with rich side information, which can help understand users and items.

Recommendation Systems

Learning Effective Embeddings From Crowdsourced Labels: An Educational Case Study

1 code implementation18 Jul 2019 Guowei Xu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu

In practice, the crowdsourced labels are usually inconsistent among crowd workers given their diverse expertise and the number of crowdsourced labels is very limited.

Representation Learning

A Novel ILP Framework for Summarizing Content with High Lexical Variety

no code implementations25 Jul 2018 Wencan Luo, Fei Liu, Zitao Liu, Diane Litman

Summarizing content contributed by individuals can be challenging, because people make different lexical choices even when describing the same events.

Abstractive Text Summarization Vocal Bursts Intensity Prediction

Automatic Summarization of Student Course Feedback

no code implementations NAACL 2016 Wencan Luo, Fei Liu, Zitao Liu, Diane Litman

Student course feedback is generated daily in both classrooms and online course discussion forums.

Sparse Linear Dynamical System with Its Application in Multivariate Clinical Time Series

no code implementations27 Nov 2013 Zitao Liu, Milos Hauskrecht

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning multivariate time series.

Time Series Time Series Analysis

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