Search Results for author: Qi Zhu

Found 50 papers, 25 papers with code

When does Further Pre-training MLM Help? An Empirical Study on Task-Oriented Dialog Pre-training

1 code implementation EMNLP (insights) 2021 Qi Zhu, Yuxian Gu, Lingxiao Luo, Bing Li, Cheng Li, Wei Peng, Minlie Huang, Xiaoyan Zhu

Further pre-training language models on in-domain data (domain-adaptive pre-training, DAPT) or task-relevant data (task-adaptive pre-training, TAPT) before fine-tuning has been shown to improve downstream tasks’ performances.

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

no code implementations22 Jun 2022 Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Štajner, Sebastien Montella, Shailza, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin Adewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou

This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.

Text Generation

Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction

no code implementations27 May 2022 Ruochen Jiao, Xiangguo Liu, Takami Sato, Qi Alfred Chen, Qi Zhu

Predicting the trajectories of surrounding objects is a critical task in self-driving and many other autonomous systems.

Adversarial Robustness Decision Making +1

Heterformer: A Transformer Architecture for Node Representation Learning on Heterogeneous Text-Rich Networks

no code implementations20 May 2022 Bowen Jin, Yu Zhang, Qi Zhu, Jiawei Han

We study node representation learning on heterogeneous text-rich networks, where nodes and edges are multi-typed and some types of nodes are associated with text information.

Graph Attention Link Prediction +4

Augmentation-Free Graph Contrastive Learning with Performance Guarantee

no code implementations11 Apr 2022 Haonan Wang, Jieyu Zhang, Qi Zhu, Wei Huang

Graph contrastive learning (GCL) is the most representative and prevalent self-supervised learning approach for graph-structured data.

Contrastive Learning Self-Supervised Learning

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

no code implementations26 Mar 2022 Zhilu Wang, Chao Huang, Qi Zhu

The robustness of deep neural networks has received significant interest recently, especially when being deployed in safety-critical systems, as it is important to analyze how sensitive the model output is under input perturbations.

Federated Class-Incremental Learning

1 code implementation CVPR 2022 Jiahua Dong, Lixu Wang, Zhen Fang, Gan Sun, Shichao Xu, Xiao Wang, Qi Zhu

It makes the global model suffer from significant catastrophic forgetting on old classes in real-world scenarios, where local clients often collect new classes continuously and have very limited storage memory to store old classes.

class-incremental learning Federated Learning +1

Continual Prompt Tuning for Dialog State Tracking

1 code implementation ACL 2022 Qi Zhu, Bing Li, Fei Mi, Xiaoyan Zhu, Minlie Huang

A desirable dialog system should be able to continually learn new skills without forgetting old ones, and thereby adapt to new domains or tasks in its life cycle.

Continual Learning Transfer Learning

Shift-Robust Node Classification via Graph Adversarial Clustering

no code implementations7 Mar 2022 Qi Zhu, Chao Zhang, Chanyoung Park, Carl Yang, Jiawei Han

Then a shift-robust classifier is optimized on training graph and adversarial samples on target graph, which are generated by cluster GNN.

Classification Domain Adaptation +1

TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor

no code implementations2 Mar 2022 Ruochen Jiao, Xiangguo Liu, Bowen Zheng, Dave Liang, Qi Zhu

Our model addresses trajectory generation and prediction in a unified architecture and benefits both tasks: the model can generate diverse, controllable and realistic trajectories to enhance planner optimization in safety-critical and long-tailed scenarios, and it can provide prediction of critical behavior in addition to the final trajectories for decision making.

Decision Making

Joint Differentiable Optimization and Verification for Certified Reinforcement Learning

no code implementations28 Jan 2022 YiXuan Wang, Chao Huang, Zhaoran Wang, Zhuoran Yang, Qi Zhu

In model-based reinforcement learning for safety-critical control systems, it is important to formally certify system properties (e. g., safety, stability) under the learned controller.

Bilevel Optimization Model-based Reinforcement Learning +1

Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data

1 code implementation NeurIPS 2021 Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi

In this work we present a method, Shift-Robust GNN (SR-GNN), designed to account for distributional differences between biased training data and the graph's true inference distribution.

Co-designing Intelligent Control of Building HVACs and Microgrids

1 code implementation18 Jul 2021 Rumia Masburah, Sayan Sinha, Rajib Lochan Jana, Soumyajit Dey, Qi Zhu

Building loads consume roughly 40% of the energy produced in developed countries, a significant part of which is invested towards building temperature-control infrastructure.

reinforcement-learning

Learning-based Framework for Sensor Fault-Tolerant Building HVAC Control with Model-assisted Learning

no code implementations27 Jun 2021 Shichao Xu, Yangyang Fu, YiXuan Wang, Zheng O'Neill, Qi Zhu

As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort and reducing energy consumption.

POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems

1 code implementation25 Jun 2021 Chao Huang, Jiameng Fan, Xin Chen, Wenchao Li, Qi Zhu

We propose POLAR, a \textbf{pol}ynomial \textbf{ar}ithmetic framework that leverages polynomial overapproximations with interval remainders for bounded-time reachability analysis of neural network-controlled systems (NNCSs).

Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization

1 code implementation ICLR 2022 Lixu Wang, Shichao Xu, Ruiqi Xu, Xiao Wang, Qi Zhu

Our NTL-based authorization approach instead provides data-centric protection, which we call applicability authorization, by significantly degrading the performance of the model on unauthorized data.

Verification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees

no code implementations6 Jun 2021 YiXuan Wang, Chao Huang, Zhaoran Wang, Zhilu Wang, Qi Zhu

Specifically, we leverage the verification results (computed reachable set of the system state) to construct feedback metrics for control learning, which measure how likely the current design of control parameters can meet the required reach-avoid property for safety and goal-reaching.

Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads

no code implementations30 Apr 2021 Chenyu Gao, Qi Zhu, Peng Wang, Qi Wu

Based on this observation, we design a dynamic chopping module that can automatically remove heads and layers of the VisualBERT at an instance level when dealing with different questions.

Question Answering Visual Question Answering +1

End-to-end Uncertainty-based Mitigation of Adversarial Attacks to Automated Lane Centering

no code implementations27 Feb 2021 Ruochen Jiao, Hengyi Liang, Takami Sato, Junjie Shen, Qi Alfred Chen, Qi Zhu

The experiment results demonstrate that our approach can effectively mitigate the impact of adversarial attacks and can achieve 55% to 90% improvement over the original OpenPilot.

Autonomous Driving

Securing Connected Vehicle Applications with an Efficient Dual Cyber-Physical Blockchain Framework

no code implementations15 Feb 2021 Xiangguo Liu, Baiting Luo, Ahmed Abdo, Nael Abu-Ghazaleh, Qi Zhu

While connected vehicle (CV) applications have the potential to revolutionize traditional transportation system, cyber and physical attacks on them could be devastating.

Cryptography and Security

Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps

1 code implementation9 Dec 2020 Qi Zhu, Chenyu Gao, Peng Wang, Qi Wu

Texts appearing in daily scenes that can be recognized by OCR (Optical Character Recognition) tools contain significant information, such as street name, product brand and prices.

Image Captioning Optical Character Recognition +2

Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization

1 code implementation NeurIPS 2021 Qi Zhu, Carl Yang, Yidan Xu, Haonan Wang, Chao Zhang, Jiawei Han

Graph neural networks (GNNs) have achieved superior performance in various applications, but training dedicated GNNs can be costly for large-scale graphs.

Knowledge Graphs Transfer Learning

Addressing Class Imbalance in Federated Learning

2 code implementations14 Aug 2020 Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu

Our experiments demonstrate the importance of acknowledging class imbalance and taking measures as early as possible in FL training, and the effectiveness of our method in mitigating the impact.

Federated Learning

Distributed Multi-agent Video Fast-forwarding

1 code implementation10 Aug 2020 Shuyue Lan, Zhilu Wang, Amit K. Roy-Chowdhury, Ermin Wei, Qi Zhu

In many intelligent systems, a network of agents collaboratively perceives the environment for better and more efficient situation awareness.

One for Many: Transfer Learning for Building HVAC Control

no code implementations9 Aug 2020 Shichao Xu, Yi-Xuan Wang, Yanzhi Wang, Zheng O'Neill, Qi Zhu

Traditional HVAC control methods are typically based on creating explicit physical models for building thermal dynamics, which often require significant effort to develop and are difficult to achieve sufficient accuracy and efficiency for runtime building control and scalability for field implementations.

Transfer Learning

Unsupervised Differentiable Multi-aspect Network Embedding

1 code implementation7 Jun 2020 Chanyoung Park, Carl Yang, Qi Zhu, Donghyun Kim, Hwanjo Yu, Jiawei Han

To capture the multiple aspects of each node, existing studies mainly rely on offline graph clustering performed prior to the actual embedding, which results in the cluster membership of each node (i. e., node aspect distribution) fixed throughout training of the embedding model.

Graph Clustering Graph Mining +1

Structured Multimodal Attentions for TextVQA

2 code implementations1 Jun 2020 Chenyu Gao, Qi Zhu, Peng Wang, Hui Li, Yuliang Liu, Anton Van Den Hengel, Qi Wu

In this paper, we propose an end-to-end structured multimodal attention (SMA) neural network to mainly solve the first two issues above.

Graph Attention Optical Character Recognition +3

Is Your Goal-Oriented Dialog Model Performing Really Well? Empirical Analysis of System-wise Evaluation

no code implementations SIGDIAL (ACL) 2020 Ryuichi Takanobu, Qi Zhu, Jinchao Li, Baolin Peng, Jianfeng Gao, Minlie Huang

There is a growing interest in developing goal-oriented dialog systems which serve users in accomplishing complex tasks through multi-turn conversations.

Goal-Oriented Dialog

Recent Advances and Challenges in Task-oriented Dialog System

no code implementations17 Mar 2020 Zheng Zhang, Ryuichi Takanobu, Qi Zhu, Minlie Huang, Xiaoyan Zhu

Due to the significance and value in human-computer interaction and natural language processing, task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.

Natural Language Processing

CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset

2 code implementations TACL 2020 Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, Minlie Huang

To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.

Dialogue State Tracking Task-Oriented Dialogue Systems

ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems

1 code implementation ACL 2020 Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang

We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems.

Task-Oriented Dialogue Systems

Eavesdrop the Composition Proportion of Training Labels in Federated Learning

no code implementations14 Oct 2019 Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu

Federated learning (FL) has recently emerged as a new form of collaborative machine learning, where a common model can be learned while keeping all the training data on local devices.

Federated Learning Inference Attack

Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity

1 code implementation4 Sep 2019 Yu Shi, Jiaming Shen, Yuchen Li, Naijing Zhang, Xinwei He, Zhengzhi Lou, Qi Zhu, Matthew Walker, Myunghwan Kim, Jiawei Han

Extensive experiments on two large real-world datasets demonstrate the effectiveness of HyperMine and the utility of modeling context granularity.

Knowledge Graphs

Facet-Aware Evaluation for Extractive Summarization

1 code implementation ACL 2020 Yuning Mao, Liyuan Liu, Qi Zhu, Xiang Ren, Jiawei Han

In this paper, we present a facet-aware evaluation setup for better assessment of the information coverage in extracted summaries.

Extractive Summarization Text Summarization

ReachNN: Reachability Analysis of Neural-Network Controlled Systems

1 code implementation25 Jun 2019 Chao Huang, Jiameng Fan, Wenchao Li, Xin Chen, Qi Zhu

In this work, we propose a new reachability analysis approach based on Bernstein polynomials that can verify neural-network controlled systems with a more general form of activation functions, i. e., as long as they ensure that the neural networks are Lipschitz continuous.

Task-Guided Pair Embedding in Heterogeneous Network

1 code implementation4 Jun 2019 Chanyoung Park, Donghyun Kim, Qi Zhu, Jiawei Han, Hwanjo Yu

In this paper, we propose a novel task-guided pair embedding framework in heterogeneous network, called TaPEm, that directly models the relationship between a pair of nodes that are related to a specific task (e. g., paper-author relationship in author identification).

Network Embedding

ConvLab: Multi-Domain End-to-End Dialog System Platform

2 code implementations ACL 2019 Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Xiang Li, Yaoqin Zhang, Zheng Zhang, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, Jianfeng Gao

We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches, ranging from conventional pipeline systems to end-to-end neural models, in common environments.

Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

1 code implementation10 Jul 2018 Yu Shi, Qi Zhu, Fang Guo, Chao Zhang, Jiawei Han

To cope with the challenges in the comprehensive transcription of HINs, we propose the HEER algorithm, which embeds HINs via edge representations that are further coupled with properly-learned heterogeneous metrics.

Feature Engineering Network Embedding

FFNet: Video Fast-Forwarding via Reinforcement Learning

1 code implementation CVPR 2018 Shuyue Lan, Rameswar Panda, Qi Zhu, Amit K. Roy-Chowdhury

The first group is supported by video summarization techniques, which require processing of the entire video to select an important subset for showing to users.

Computer Vision reinforcement-learning +1

Integrating Local Context and Global Cohesiveness for Open Information Extraction

1 code implementation26 Apr 2018 Qi Zhu, Xiang Ren, Jingbo Shang, Yu Zhang, Ahmed El-Kishky, Jiawei Han

However, current Open IE systems focus on modeling local context information in a sentence to extract relation tuples, while ignoring the fact that global statistics in a large corpus can be collectively leveraged to identify high-quality sentence-level extractions.

Open Information Extraction

Expert Finding in Heterogeneous Bibliographic Networks with Locally-trained Embeddings

no code implementations9 Mar 2018 Huan Gui, Qi Zhu, Liyuan Liu, Aston Zhang, Jiawei Han

We study the task of expert finding in heterogeneous bibliographical networks based on two aspects: textual content analysis and authority ranking.

AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks

no code implementations5 Mar 2018 Yu Shi, Huan Gui, Qi Zhu, Lance Kaplan, Jiawei Han

Therefore, we are motivated to propose a novel embedding learning framework---AspEm---to preserve the semantic information in HINs based on multiple aspects.

Link Prediction Network Embedding

Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations

no code implementations10 Oct 2017 Hongjia Li, Tianshu Wei, Ao Ren, Qi Zhu, Yanzhi Wang

The recent breakthroughs of deep reinforcement learning (DRL) technique in Alpha Go and playing Atari have set a good example in handling large state and actions spaces of complicated control problems.

Q-Learning reinforcement-learning

Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach

1 code implementation EMNLP 2017 Liyuan Liu, Xiang Ren, Qi Zhu, Shi Zhi, Huan Gui, Heng Ji, Jiawei Han

These annotations, referred as heterogeneous supervision, often conflict with each other, which brings a new challenge to the original relation extraction task: how to infer the true label from noisy labels for a given instance.

Relation Extraction Representation Learning

Adaptive Algorithm and Platform Selection for Visual Detection and Tracking

no code implementations21 May 2016 Shu Zhang, Qi Zhu, Amit Roy-Chowdhury

In this paper, we focus on this problem and propose a framework to adaptively select the "best" algorithm-parameter combination and the computation platform under performance and cost constraints at design time, and adapt the algorithms at runtime based on real-time inputs.

Computer Vision Pedestrian Detection

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