Search Results for author: Zitao Liu

Found 50 papers, 26 papers with code

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

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

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.

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 Text Classification

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

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

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

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.

Classification Fairness +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.

Contrastive Learning Incomplete multi-view clustering +1

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.

Contrastive Learning Online Clustering

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.

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

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

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.

online 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.

Fairness

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

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.

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

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.

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

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

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

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

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