Search Results for author: Xin Zheng

Found 32 papers, 10 papers with code

Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning

no code implementations26 Feb 2024 Man Wu, Xin Zheng, Qin Zhang, Xiao Shen, Xiong Luo, Xingquan Zhu, Shirui Pan

Graph learning plays a pivotal role and has gained significant attention in various application scenarios, from social network analysis to recommendation systems, for its effectiveness in modeling complex data relations represented by graph structural data.

Continual Learning Domain Adaptation +2

Traj-LIO: A Resilient Multi-LiDAR Multi-IMU State Estimator Through Sparse Gaussian Process

no code implementations14 Feb 2024 Xin Zheng, Jianke Zhu

Nowadays, sensor suits have been equipped with redundant LiDARs and IMUs to mitigate the risks associated with sensor failure.

ViP-Mixer: A Convolutional Mixer for Video Prediction

no code implementations20 Nov 2023 Xin Zheng, Ziang Peng, Yuan Cao, Hongming Shan, Junping Zhang

Video prediction aims to predict future frames from a video's previous content.

Video Prediction

Graph Neural Architecture Search with GPT-4

no code implementations30 Sep 2023 Haishuai Wang, Yang Gao, Xin Zheng, Peng Zhang, Hongyang Chen, Jiajun Bu

In this paper, we integrate GPT-4 into GNAS and propose a new GPT-4 based Graph Neural Architecture Search method (GPT4GNAS for short).

Neural Architecture Search

Traj-LO: In Defense of LiDAR-Only Odometry Using an Effective Continuous-Time Trajectory

1 code implementation25 Sep 2023 Xin Zheng, Jianke Zhu

Therefore, our proposed Traj-LO approach tries to recover the spatial-temporal consistent movement of LiDAR by tightly coupling the geometric information from LiDAR points and kinematic constraints from trajectory smoothness.

Towards Data-centric Graph Machine Learning: Review and Outlook

1 code implementation20 Sep 2023 Xin Zheng, Yixin Liu, Zhifeng Bao, Meng Fang, Xia Hu, Alan Wee-Chung Liew, Shirui Pan

Data-centric AI, with its primary focus on the collection, management, and utilization of data to drive AI models and applications, has attracted increasing attention in recent years.

Management Navigate

Toward Unified Controllable Text Generation via Regular Expression Instruction

1 code implementation19 Sep 2023 Xin Zheng, Hongyu Lin, Xianpei Han, Le Sun

Controllable text generation is a fundamental aspect of natural language generation, with numerous methods proposed for different constraint types.

In-Context Learning Text Generation

Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model

no code implementations17 Jun 2023 Jiaan Wang, Jianfeng Qu, Yunlong Liang, Zhixu Li, An Liu, Guanfeng Liu, Xin Zheng

Constructing commonsense knowledge graphs (CKGs) has attracted wide research attention due to its significant importance in cognitive intelligence.

Knowledge Graphs

Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data

1 code implementation NeurIPS 2023 Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan

Specifically, SFGC contains two collaborative components: (1) a training trajectory meta-matching scheme for effectively synthesizing small-scale graph-free data; (2) a graph neural feature score metric for dynamically evaluating the quality of the condensed data.

Graph Learning

DialogVCS: Robust Natural Language Understanding in Dialogue System Upgrade

no code implementations24 May 2023 Zefan Cai, Xin Zheng, Tianyu Liu, Xu Wang, Haoran Meng, Jiaqi Han, Gang Yuan, Binghuai Lin, Baobao Chang, Yunbo Cao

In the constant updates of the product dialogue systems, we need to retrain the natural language understanding (NLU) model as new data from the real users would be merged into the existent data accumulated in the last updates.

Intent Detection Multi-Label Classification +1

Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs

no code implementations23 Feb 2023 Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan

Therefore, in this paper, we propose a novel automated graph neural network on heterophilic graphs, namely Auto-HeG, to automatically build heterophilic GNN models with expressive learning abilities.

Graph Learning Neural Architecture Search

DialogQAE: N-to-N Question Answer Pair Extraction from Customer Service Chatlog

no code implementations14 Dec 2022 Xin Zheng, Tianyu Liu, Haoran Meng, Xu Wang, Yufan Jiang, Mengliang Rao, Binghuai Lin, Zhifang Sui, Yunbo Cao

Harvesting question-answer (QA) pairs from customer service chatlog in the wild is an efficient way to enrich the knowledge base for customer service chatbots in the cold start or continuous integration scenarios.


What Knowledge Is Needed? Towards Explainable Memory for kNN-MT Domain Adaptation

1 code implementation8 Nov 2022 Wenhao Zhu, ShuJian Huang, Yunzhe Lv, Xin Zheng, Jiajun Chen

kNN-MT presents a new paradigm for domain adaptation by building an external datastore, which usually saves all target language token occurrences in the parallel corpus.

Domain Adaptation NMT +1

Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis

no code implementations28 Oct 2022 Peipei Liu, Xin Zheng, Hong Li, Jie Liu, Yimo Ren, Hongsong Zhu, Limin Sun

At the second stage, a self-supervised contrastive learning is designed for the improvement of the distilled unimodal representations after cross-modal interaction.

Contrastive Learning Multimodal Sentiment Analysis +1

ECTLO: Effective Continuous-time Odometry Using Range Image for LiDAR with Small FoV

1 code implementation17 Jun 2022 Xin Zheng, Jianke Zhu

Prism-based LiDARs are more compact and cheaper than the conventional mechanical multi-line spinning LiDARs, which have become increasingly popular in robotics, recently.

Autonomous Driving

Graph Neural Networks for Graphs with Heterophily: A Survey

no code implementations14 Feb 2022 Xin Zheng, Yi Wang, Yixin Liu, Ming Li, Miao Zhang, Di Jin, Philip S. Yu, Shirui Pan

In the end, we point out the potential directions to advance and stimulate more future research and applications on heterophilic graph learning with GNNs.

Graph Learning

Robust Physical-World Attacks on Face Recognition

no code implementations20 Sep 2021 Xin Zheng, Yanbo Fan, Baoyuan Wu, Yong Zhang, Jue Wang, Shirui Pan

Face recognition has been greatly facilitated by the development of deep neural networks (DNNs) and has been widely applied to many safety-critical applications.

Adversarial Attack Adversarial Robustness +1

Non-Parametric Unsupervised Domain Adaptation for Neural Machine Translation

1 code implementation Findings (EMNLP) 2021 Xin Zheng, Zhirui Zhang, ShuJian Huang, Boxing Chen, Jun Xie, Weihua Luo, Jiajun Chen

Recently, $k$NN-MT has shown the promising capability of directly incorporating the pre-trained neural machine translation (NMT) model with domain-specific token-level $k$-nearest-neighbor ($k$NN) retrieval to achieve domain adaptation without retraining.

Machine Translation NMT +3

Adaptive Nearest Neighbor Machine Translation

3 code implementations ACL 2021 Xin Zheng, Zhirui Zhang, Junliang Guo, ShuJian Huang, Boxing Chen, Weihua Luo, Jiajun Chen

On four benchmark machine translation datasets, we demonstrate that the proposed method is able to effectively filter out the noises in retrieval results and significantly outperforms the vanilla kNN-MT model.

Machine Translation NMT +2

Efficient LiDAR Odometry for Autonomous Driving

no code implementations22 Apr 2021 Xin Zheng, Jianke Zhu

LiDAR odometry plays an important role in self-localization and mapping for autonomous navigation, which is usually treated as a scan registration problem.

Autonomous Driving Autonomous Navigation

Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View

1 code implementation17 Feb 2021 Tianyu Liu, Xin Zheng, Baobao Chang, Zhifang Sui

In open domain table-to-text generation, we notice that the unfaithful generation usually contains hallucinated content which can not be aligned to any input table record.

Few-Shot Learning Table-to-Text Generation

Neural Network Compression for Noisy Storage Devices

no code implementations15 Feb 2021 Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi

Compression and efficient storage of neural network (NN) parameters is critical for applications that run on resource-constrained devices.

Neural Network Compression

An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference

1 code implementation CONLL 2020 Tianyu Liu, Xin Zheng, Xiaoan Ding, Baobao Chang, Zhifang Sui

The prior work on natural language inference (NLI) debiasing mainly targets at one or few known biases while not necessarily making the models more robust.

Data Augmentation Natural Language Inference

HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference

no code implementations LREC 2020 Tianyu Liu, Xin Zheng, Baobao Chang, Zhifang Sui

Many recent studies have shown that for models trained on datasets for natural language inference (NLI), it is possible to make correct predictions by merely looking at the hypothesis while completely ignoring the premise.

Natural Language Inference Test

Two-dimensional Multi-fiber Spectrum Image Correction Based on Machine Learning Techniques

no code implementations16 Feb 2020 Jiali Xu, Qian Yin, Ping Guo, Xin Zheng

At the same time, the spectrum extraction results before and after calibration are compared, results show the characteristics of the extracted one-dimensional waveform are more close to an ideal optics system, and the PSF of the corrected object spectrum image estimated by the blind deconvolution method is nearly central symmetry, which indicates that our proposed method can significantly reduce the complexity of spectrum extraction and improve extraction accuracy.

BIG-bench Machine Learning

Subtopic-driven Multi-Document Summarization

no code implementations IJCNLP 2019 Xin Zheng, Aixin Sun, Jing Li, Karthik Muthuswamy

In multi-document summarization, a set of documents to be summarized is assumed to be on the same topic, known as the underlying topic in this paper.

Document Summarization Multi-Document Summarization +1

A Survey of Deep Facial Attribute Analysis

no code implementations26 Dec 2018 Xin Zheng, Yanqing Guo, Huaibo Huang, Yi Li, Ran He

Deep learning based facial attribute analysis consists of two basic sub-issues: facial attribute estimation (FAE), which recognizes whether facial attributes are present in given images, and facial attribute manipulation (FAM), which synthesizes or removes desired facial attributes.


Character-Based Text Classification using Top Down Semantic Model for Sentence Representation

no code implementations29 May 2017 Zhenzhou Wu, Xin Zheng, Daniel Dahlmeier

Despite the success of deep learning on many fronts especially image and speech, its application in text classification often is still not as good as a simple linear SVM on n-gram TF-IDF representation especially for smaller datasets.

General Classification Sentence +2

A Survey of Location Prediction on Twitter

no code implementations9 May 2017 Xin Zheng, Jialong Han, Aixin Sun

Specifically, we concentrate on the prediction of user home locations, tweet locations, and mentioned locations.

point of interests

Application of Deep Neural Network in Estimation of the Weld Bead Parameters

no code implementations14 Feb 2015 Soheil Keshmiri, Xin Zheng, Chee Meng Chew, Chee Khiang Pang

We present a deep learning approach to estimation of the bead parameters in welding tasks.

Feature Learning with Gaussian Restricted Boltzmann Machine for Robust Speech Recognition

no code implementations23 Sep 2013 Xin Zheng, Zhiyong Wu, Helen Meng, Weifeng Li, Lianhong Cai

In this paper, we first present a new variant of Gaussian restricted Boltzmann machine (GRBM) called multivariate Gaussian restricted Boltzmann machine (MGRBM), with its definition and learning algorithm.

Robust Speech Recognition speech-recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.