Search Results for author: Xin Zhou

Found 80 papers, 29 papers with code

Making Parameter-efficient Tuning More Efficient: A Unified Framework for Classification Tasks

1 code implementation COLING 2022 Xin Zhou, Ruotian Ma, Yicheng Zou, Xuanting Chen, Tao Gui, Qi Zhang, Xuanjing Huang, Rui Xie, Wei Wu

Specifically, we re-formulate both token and sentence classification tasks into a unified language modeling task, and map label spaces of different tasks into the same vocabulary space.

Language Modelling Sentence Classification +1

LFKQG: A Controlled Generation Framework with Local Fine-tuning for Question Generation over Knowledge Bases

no code implementations COLING 2022 Zichu Fei, Xin Zhou, Tao Gui, Qi Zhang, Xuanjing Huang

Existing KBQG models still face two main challenges: (1) Most models often focus on the most relevant part of the answer entity, while neglecting the rest of the subgraph.

Natural Questions Question Generation +1

Retrieving Conditions from Reference Images for Diffusion Models

no code implementations5 Dec 2023 Haoran Tang, Xin Zhou, Jieren Deng, Zhihong Pan, Hao Tian, Pratik Chaudhari

Finally, we provide baseline experiment results on new tasks, and conduct ablation studies on the possible structural choices.

Hypergraph Node Representation Learning with One-Stage Message Passing

no code implementations1 Dec 2023 Shilin Qu, Weiqing Wang, Yuan-Fang Li, Xin Zhou, Fajie Yuan

HGraphormer injects the hypergraph structure information (local information) into Transformers (global information) by combining the attention matrix and hypergraph Laplacian.

Representation Learning

AviationGPT: A Large Language Model for the Aviation Domain

no code implementations29 Nov 2023 Liya Wang, Jason Chou, Xin Zhou, Alex Tien, Diane M Baumgartner

The advent of ChatGPT and GPT-4 has captivated the world with large language models (LLMs), demonstrating exceptional performance in question-answering, summarization, and content generation.

Language Modelling Large Language Model +1

Attributes Grouping and Mining Hashing for Fine-Grained Image Retrieval

no code implementations10 Nov 2023 Xin Lu, Shikun Chen, Yichao Cao, Xin Zhou, Xiaobo Lu

To handle this limitation, we substitute convolutional descriptors for attention-guided features and propose an Attributes Grouping and Mining Hashing (AGMH), which groups and embeds the category-specific visual attributes in multiple descriptors to generate a comprehensive feature representation for efficient fine-grained image retrieval.

Image Retrieval Retrieval

Making Harmful Behaviors Unlearnable for Large Language Models

no code implementations2 Nov 2023 Xin Zhou, Yi Lu, Ruotian Ma, Tao Gui, Qi Zhang, Xuanjing Huang

Specifically, we introduce ``security vectors'', a few new parameters that can be separated from the LLM, to ensure LLM's responses are consistent with the harmful behavior.

Rethinking Negative Pairs in Code Search

1 code implementation12 Oct 2023 Haochen Li, Xin Zhou, Luu Anh Tuan, Chunyan Miao

In our proposed loss function, we apply three methods to estimate the weights of negative pairs and show that the vanilla InfoNCE loss is a special case of Soft-InfoNCE.

Code Search Contrastive Learning +2

SOFARI: High-Dimensional Manifold-Based Inference

no code implementations26 Sep 2023 Zemin Zheng, Xin Zhou, Yingying Fan, Jinchi Lv

In this paper, we suggest a novel approach called high-dimensional manifold-based SOFAR inference (SOFARI), drawing on the Neyman near-orthogonality inference while incorporating the Stiefel manifold structure imposed by the SVD constraints.

Multi-Task Learning

SoccerNet 2023 Challenges Results

1 code implementation12 Sep 2023 Anthony Cioppa, Silvio Giancola, Vladimir Somers, Floriane Magera, Xin Zhou, Hassan Mkhallati, Adrien Deliège, Jan Held, Carlos Hinojosa, Amir M. Mansourian, Pierre Miralles, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdullah Kamal, Adrien Maglo, Albert Clapés, Amr Abdelaziz, Artur Xarles, Astrid Orcesi, Atom Scott, Bin Liu, Byoungkwon Lim, Chen Chen, Fabian Deuser, Feng Yan, Fufu Yu, Gal Shitrit, Guanshuo Wang, Gyusik Choi, Hankyul Kim, Hao Guo, Hasby Fahrudin, Hidenari Koguchi, Håkan Ardö, Ibrahim Salah, Ido Yerushalmy, Iftikar Muhammad, Ikuma Uchida, Ishay Be'ery, Jaonary Rabarisoa, Jeongae Lee, Jiajun Fu, Jianqin Yin, Jinghang Xu, Jongho Nang, Julien Denize, Junjie Li, Junpei Zhang, Juntae Kim, Kamil Synowiec, Kenji Kobayashi, Kexin Zhang, Konrad Habel, Kota Nakajima, Licheng Jiao, Lin Ma, Lizhi Wang, Luping Wang, Menglong Li, Mengying Zhou, Mohamed Nasr, Mohamed Abdelwahed, Mykola Liashuha, Nikolay Falaleev, Norbert Oswald, Qiong Jia, Quoc-Cuong Pham, Ran Song, Romain Hérault, Rui Peng, Ruilong Chen, Ruixuan Liu, Ruslan Baikulov, Ryuto Fukushima, Sergio Escalera, Seungcheon Lee, Shimin Chen, Shouhong Ding, Taiga Someya, Thomas B. Moeslund, Tianjiao Li, Wei Shen, Wei zhang, Wei Li, Wei Dai, Weixin Luo, Wending Zhao, Wenjie Zhang, Xinquan Yang, Yanbiao Ma, Yeeun Joo, Yingsen Zeng, Yiyang Gan, Yongqiang Zhu, Yujie Zhong, Zheng Ruan, Zhiheng Li, Zhijian Huang, Ziyu Meng

More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.

Action Spotting Camera Calibration +3

ABS-SGD: A Delayed Synchronous Stochastic Gradient Descent Algorithm with Adaptive Batch Size for Heterogeneous GPU Clusters

no code implementations29 Aug 2023 Xin Zhou, Ling Chen, Houming Wu

In this paper, we propose a delayed synchronous SGD algorithm with adaptive batch size (ABS-SGD) for heterogeneous GPU clusters.

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models

no code implementations21 Aug 2023 Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari Sahraoui

Large Language Models (LLMs) possess impressive capabilities to generate meaningful code snippets given natural language intents in zero-shot, i. e., without the need for specific fine-tuning.

Code Generation

Better Zero-Shot Reasoning with Role-Play Prompting

1 code implementation15 Aug 2023 Aobo Kong, Shiwan Zhao, Hao Chen, Qicheng Li, Yong Qin, Ruiqi Sun, Xin Zhou

This highlights its potential to augment the reasoning capabilities of LLMs.

Encoding Enhanced Complex CNN for Accurate and Highly Accelerated MRI

no code implementations21 Jun 2023 Zimeng Li, Sa Xiao, Cheng Wang, Haidong Li, Xiuchao Zhao, Caohui Duan, Qian Zhou, Qiuchen Rao, Yuan Fang, Junshuai Xie, Lei Shi, Fumin Guo, Chaohui Ye, Xin Zhou

Magnetic resonance imaging (MRI) using hyperpolarized noble gases provides a way to visualize the structure and function of human lung, but the long imaging time limits its broad research and clinical applications.

MRI Reconstruction

GBSD: Generative Bokeh with Stage Diffusion

no code implementations14 Jun 2023 Jieren Deng, Xin Zhou, Hao Tian, Zhihong Pan, Derek Aguiar

The bokeh effect is an artistic technique that blurs out-of-focus areas in a photograph and has gained interest due to recent developments in text-to-image synthesis and the ubiquity of smart-phone cameras and photo-sharing apps.

Image Generation Image Manipulation +1

Sequential Best-Arm Identification with Application to Brain-Computer Interface

no code implementations17 May 2023 Xin Zhou, Botao Hao, Jian Kang, Tor Lattimore, Lexin Li

A brain-computer interface (BCI) is a technology that enables direct communication between the brain and an external device or computer system.

EEG Electroencephalogram (EEG) +2

On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code

no code implementations6 May 2023 Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari Sahraoui

We demonstrate that the most commonly used fine-tuning technique from prior work is not robust enough to handle the dynamic nature of APIs, leading to the loss of previously acquired knowledge i. e., catastrophic forgetting.

Continual Learning General Knowledge +1

Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis

no code implementations22 Apr 2023 Yansong Gao, Zhihong Pan, Xin Zhou, Le Kang, Pratik Chaudhari

This work analyzes how the backward error affects the diffusion ODEs and the sample quality in DDPMs.


Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning

no code implementations21 Mar 2023 Lingzi Zhang, Xin Zhou, Zhiqi Shen

To address this issue, we propose a novel pre-training framework, named Multimodal Sequence Mixup for Sequential Recommendation (MSM4SR), which leverages both users' sequential behaviors and items' multimodal content (\ie text and images) for effectively recommendation.

Contrastive Learning Sequential Recommendation

Raising The Limit Of Image Rescaling Using Auxiliary Encoding

no code implementations12 Mar 2023 Chenzhong Yin, Zhihong Pan, Xin Zhou, Le Kang, Paul Bogdan

While the random sampling of latent variable $z$ is useful in generating diverse photo-realistic images, it is not desirable for image rescaling when accurate restoration of the HR image is more important.

Image Super-Resolution

Smooth and Stepwise Self-Distillation for Object Detection

no code implementations9 Mar 2023 Jieren Deng, Xin Zhou, Hao Tian, Zhihong Pan, Derek Aguiar

Distilling the structured information captured in feature maps has contributed to improved results for object detection tasks, but requires careful selection of baseline architectures and substantial pre-training.

object-detection Object Detection

Do We Really Need Complicated Model Architectures For Temporal Networks?

no code implementations22 Feb 2023 Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi

Recurrent neural network (RNN) and self-attention mechanism (SAM) are the de facto methods to extract spatial-temporal information for temporal graph learning.

Graph Learning Link Prediction

EC-SfM: Efficient Covisibility-based Structure-from-Motion for Both Sequential and Unordered Images

1 code implementation21 Feb 2023 Zhichao Ye, Chong Bao, Xin Zhou, Haomin Liu, Hujun Bao, Guofeng Zhang

Based on this general image connection, we propose a unified framework to efficiently reconstruct sequential images, unordered images, and the mixture of these two.

Dual Graph Multitask Framework for Imbalanced Delivery Time Estimation

no code implementations15 Feb 2023 Lei Zhang, Mingliang Wang, Xin Zhou, Xingyu Wu, Yiming Cao, Yonghui Xu, Lizhen Cui, Zhiqi Shen

To address the issue, we propose a novel Dual Graph Multitask framework for imbalanced Delivery Time Estimation (DGM-DTE).

A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

1 code implementation9 Feb 2023 HongYu Zhou, Xin Zhou, Zhiwei Zeng, Lingzi Zhang, Zhiqi Shen

Recommendation systems have become popular and effective tools to help users discover their interesting items by modeling the user preference and item property based on implicit interactions (e. g., purchasing and clicking).

Recommendation Systems

MMRec: Simplifying Multimodal Recommendation

1 code implementation2 Feb 2023 Xin Zhou

This paper presents an open-source toolbox, MMRec for multimodal recommendation.

Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation

1 code implementation28 Jan 2023 HongYu Zhou, Xin Zhou, Lingzi Zhang, Zhiqi Shen

On top of the finding, we propose a model that enhances the dyadic relations by learning Dual RepresentAtions of both users and items via constructing homogeneous Graphs for multimOdal recommeNdation.

Graph Learning Recommendation Systems

Arbitrary Style Guidance for Enhanced Diffusion-Based Text-to-Image Generation

no code implementations14 Nov 2022 Zhihong Pan, Xin Zhou, Hao Tian

Diffusion-based text-to-image generation models like GLIDE and DALLE-2 have gained wide success recently for their superior performance in turning complex text inputs into images of high quality and wide diversity.

Style Transfer

Extreme Generative Image Compression by Learning Text Embedding from Diffusion Models

no code implementations14 Nov 2022 Zhihong Pan, Xin Zhou, Hao Tian

With the recent success of diffusion models for text-to-image generation, we propose a generative image compression method that demonstrates the potential of saving an image as a short text embedding which in turn can be used to generate high-fidelity images which is equivalent to the original one perceptually.

Image Compression

A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation

2 code implementations13 Nov 2022 Xin Zhou, Zhiqi Shen

Based on this finding, we propose a simple yet effective model, dubbed as FREEDOM, that FREEzes the item-item graph and DenOises the user-item interaction graph simultaneously for Multimodal recommendation.

Denoising Graph structure learning +1

Inductive Graph Transformer for Delivery Time Estimation

1 code implementation5 Nov 2022 Xin Zhou, Jinglong Wang, Yong liu, Xingyu Wu, Zhiqi Shen, Cyril Leung

Providing accurate estimated time of package delivery on users' purchasing pages for e-commerce platforms is of great importance to their purchasing decisions and post-purchase experiences.

Diffusion Motion: Generate Text-Guided 3D Human Motion by Diffusion Model

no code implementations22 Oct 2022 Zhiyuan Ren, Zhihong Pan, Xin Zhou, Le Kang

We propose a simple and novel method for generating 3D human motion from complex natural language sentences, which describe different velocity, direction and composition of all kinds of actions.

Denoising Image Generation +1

Machine Learning for a Sustainable Energy Future

no code implementations19 Oct 2022 Zhenpeng Yao, Yanwei Lum, Andrew Johnston, Luis Martin Mejia-Mendoza, Xin Zhou, Yonggang Wen, Alan Aspuru-Guzik, Edward H. Sargent, Zhi Wei Seh

Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances at the levels of materials, devices, and systems for the efficient harvesting, storage, conversion, and management of renewable energy.


Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER

no code implementations10 Oct 2022 Ruotian Ma, Xuanting Chen, Lin Zhang, Xin Zhou, Junzhe Wang, Tao Gui, Qi Zhang, Xiang Gao, Yunwen Chen

In this work, we conduct an empirical study on the "Unlabeled Entity Problem" and find that it leads to severe confusion between "O" and entities, decreasing class discrimination of old classes and declining the model's ability to learn new classes.

Class Incremental Learning Contrastive Learning +3

SoccerNet 2022 Challenges Results

7 code implementations5 Oct 2022 Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.

Action Spotting Camera Calibration +3

Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural Network

no code implementations24 Jul 2022 Min Zhang, Zhihong Pan, Xin Zhou, C. -C. Jay Kuo

Normalizing flow models have been used successfully for generative image super-resolution (SR) by approximating complex distribution of natural images to simple tractable distribution in latent space through Invertible Neural Networks (INN).

Image Restoration Image Super-Resolution

Layer-refined Graph Convolutional Networks for Recommendation

1 code implementation22 Jul 2022 Xin Zhou, Donghui Lin, Yong liu, Chunyan Miao

Specifically, these models usually aggregate all layer embeddings for node updating and achieve their best recommendation performance within a few layers because of over-smoothing.

Bootstrap Latent Representations for Multi-modal Recommendation

2 code implementations13 Jul 2022 Xin Zhou, HongYu Zhou, Yong liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You, Feijun Jiang

Besides the user-item interaction graph, existing state-of-the-art methods usually use auxiliary graphs (e. g., user-user or item-item relation graph) to augment the learned representations of users and/or items.

SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos

no code implementations14 Apr 2022 Anthony Cioppa, Silvio Giancola, Adrien Deliege, Le Kang, Xin Zhou, Zhiyu Cheng, Bernard Ghanem, Marc Van Droogenbroeck

Tracking objects in soccer videos is extremely important to gather both player and team statistics, whether it is to estimate the total distance run, the ball possession or the team formation.

Benchmarking Multiple Object Tracking

Predicting and Explaining Mobile UI Tappability with Vision Modeling and Saliency Analysis

1 code implementation5 Apr 2022 Eldon Schoop, Xin Zhou, Gang Li, Zhourong Chen, Björn Hartmann, Yang Li

We use a deep learning based approach to predict whether a selected element in a mobile UI screenshot will be perceived by users as tappable, based on pixels only instead of view hierarchies required by previous work.

ASM-Loc: Action-aware Segment Modeling for Weakly-Supervised Temporal Action Localization

1 code implementation CVPR 2022 Bo He, Xitong Yang, Le Kang, Zhiyu Cheng, Xin Zhou, Abhinav Shrivastava

Without the boundary information of action segments, existing methods mostly rely on multiple instance learning (MIL), where the predictions of unlabeled instances (i. e., video snippets) are supervised by classifying labeled bags (i. e., untrimmed videos).

Weakly Supervised Temporal Action Localization

Carrier Phase Ranging for Indoor Positioning with 5G NR Signals

no code implementations22 Dec 2021 Liang Chen, Xin Zhou, Feifei Chen, Lie-Liang Yang, Ruizhi Chen

Indoor positioning is one of the core technologies of Internet of Things (IoT) and artificial intelligence (AI), and is expected to play a significant role in the upcoming era of AI.

VUT: Versatile UI Transformer for Multi-Modal Multi-Task User Interface Modeling

no code implementations10 Dec 2021 Yang Li, Gang Li, Xin Zhou, Mostafa Dehghani, Alexey Gritsenko

Our model consists of a multimodal Transformer encoder that jointly encodes UI images and structures, and performs UI object detection when the UI structures are absent in the input.

object-detection Object Detection +2

Plug-Tagger: A Pluggable Sequence Labeling Framework Using Language Models

no code implementations14 Oct 2021 Xin Zhou, Ruotian Ma, Tao Gui, Yiding Tan, Qi Zhang, Xuanjing Huang

Specifically, for each task, a label word set is first constructed by selecting a high-frequency word for each class respectively, and then, task-specific vectors are inserted into the inputs and optimized to manipulate the model predictions towards the corresponding label words.

Language Modelling Text Generation

Creating User Interface Mock-ups from High-Level Text Descriptions with Deep-Learning Models

no code implementations14 Oct 2021 Forrest Huang, Gang Li, Xin Zhou, John F. Canny, Yang Li

The design process of user interfaces (UIs) often begins with articulating high-level design goals.


VUT: Versatile UI Transformer for Multimodal Multi-Task User Interface Modeling

no code implementations29 Sep 2021 Yang Li, Gang Li, Xin Zhou, Mostafa Dehghani, Alexey A. Gritsenko

Our model consists of a multimodal Transformer encoder that jointly encodes UI images and structures, and performs UI object detection when the UI structures are absent in the input.

object-detection Object Detection +2

Template-free Prompt Tuning for Few-shot NER

1 code implementation NAACL 2022 Ruotian Ma, Xin Zhou, Tao Gui, Yiding Tan, Linyang Li, Qi Zhang, Xuanjing Huang

Prompt-based methods have been successfully applied in sentence-level few-shot learning tasks, mostly owing to the sophisticated design of templates and label words.

Few-Shot Learning Few-shot NER

Large-Scale Modeling of Mobile User Click Behaviors Using Deep Learning

no code implementations11 Aug 2021 Xin Zhou, Yang Li

Modeling tap or click sequences of users on a mobile device can improve our understandings of interaction behavior and offers opportunities for UI optimization by recommending next element the user might want to click on.

Screen2Words: Automatic Mobile UI Summarization with Multimodal Learning

2 code implementations7 Aug 2021 Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, Yang Li

Mobile User Interface Summarization generates succinct language descriptions of mobile screens for conveying important contents and functionalities of the screen, which can be useful for many language-based application scenarios.

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

2 code implementations7 Jul 2021 Xin Zhou, Aixin Sun, Yong liu, Jie Zhang, Chunyan Miao

Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions.

Collaborative Filtering Self-Supervised Learning

Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal Detection

2 code implementations28 Jun 2021 Xin Zhou, Le Kang, Zhiyu Cheng, Bo He, Jingyu Xin

With rapidly evolving internet technologies and emerging tools, sports related videos generated online are increasing at an unprecedentedly fast pace.

Action Recognition Action Spotting +3

No Need for Interactions: Robust Model-Based Imitation Learning using Neural ODE

1 code implementation3 Apr 2021 HaoChih Lin, Baopu Li, Xin Zhou, Jiankun Wang, Max Q. -H. Meng

Interactions with either environments or expert policies during training are needed for most of the current imitation learning (IL) algorithms.

Imitation Learning

Existence of constant mean curvature 2-spheres in Riemannian 3-spheres

no code implementations24 Dec 2020 Da Rong Cheng, Xin Zhou

We prove the existence of branched immersed constant mean curvature 2-spheres in an arbitrary Riemannian 3-sphere for almost every prescribed mean curvature, and moreover for all prescribed mean curvatures when the 3-sphere is positively curved.

Differential Geometry Analysis of PDEs

Distances to molecular clouds in the second Galactic quadrant

no code implementations17 Dec 2020 Qing-Zeng Yan, Ji Yang, Yan Sun, Yang Su, Ye Xu, Hongchi Wang, Xin Zhou, Chen Wang

We present distances to 76 medium-sized molecular clouds and an extra large-scale one in the second Galactic quadrant ($104. 75^\circ <l<150. 25^\circ $ and $|b|<5. 25^\circ$), 73 of which are accurately measured for the first time.

Astrophysics of Galaxies

Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions

no code implementations9 Dec 2020 Jun Wang, Shaoguo Wen, Kaixing Chen, Jianghua Yu, Xin Zhou, Peng Gao, Changsheng Li, Guotong Xie

Active learning generally involves querying the most representative samples for human labeling, which has been widely studied in many fields such as image classification and object detection.

Active Learning Image Classification +5

Cross Copy Network for Dialogue Generation

1 code implementation EMNLP 2020 Changzhen Ji, Xin Zhou, Yating Zhang, Xiaozhong Liu, Changlong Sun, Conghui Zhu, Tiejun Zhao

In the past few years, audiences from different fields witness the achievements of sequence-to-sequence models (e. g., LSTM+attention, Pointer Generator Networks, and Transformer) to enhance dialogue content generation.

Dialogue Generation

AI-lead Court Debate Case Investigation

no code implementations22 Oct 2020 Changzhen Ji, Xin Zhou, Conghui Zhu, Tiejun Zhao

The multi-role judicial debate composed of the plaintiff, defendant, and judge is an important part of the judicial trial.

Question Generation Question-Generation +1

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models

no code implementations22 Sep 2020 Alexis Cooper, Xin Zhou, Scott Heidbrink, Daniel M. Dunlavy

Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems.

Benchmarking BIG-bench Machine Learning +3

EGO-Planner: An ESDF-free Gradient-based Local Planner for Quadrotors

2 code implementations20 Aug 2020 Xin Zhou, Zhepei Wang, Chao Xu, Fei Gao

Gradient-based planners are widely used for quadrotor local planning, in which a Euclidean Signed Distance Field (ESDF) is crucial for evaluating gradient magnitude and direction.


CMPCC: Corridor-based Model Predictive Contouring Control for Aggressive Drone Flight

1 code implementation7 Jul 2020 Jialin Ji, Xin Zhou, Chao Xu, Fei Gao

In this paper, we propose an efficient, receding horizon, local adaptive low-level planner as the middle layer between our original planner and controller.


An Efficient Smoothing Proximal Gradient Algorithm for Convex Clustering

no code implementations22 Jun 2020 Xin Zhou, Chunlei Du, Xiaodong Cai

Our Sproga is faster than ADMM- or AMA-based convex clustering algorithms by one to two orders of magnitude.


Mapping Natural Language Instructions to Mobile UI Action Sequences

2 code implementations ACL 2020 Yang Li, Jiacong He, Xin Zhou, Yuan Zhang, Jason Baldridge

We present a new problem: grounding natural language instructions to mobile user interface actions, and create three new datasets for it.

Kalibre: Knowledge-based Neural Surrogate Model Calibration for Data Center Digital Twins

no code implementations29 Jan 2020 Ruihang Wang, Xin Zhou, Linsen Dong, Yonggang Wen, Rui Tan, Li Chen, Guan Wang, Feng Zeng

However, in the context of CFD, each search step requires long-lasting CFD model's iterated solving, rendering these approaches impractical with increased model complexity.


Auto Completion of User Interface Layout Design Using Transformer-Based Tree Decoders

no code implementations14 Jan 2020 Yang Li, Julien Amelot, Xin Zhou, Samy Bengio, Si Si

While we focus on interface layout prediction, our model can be generally applicable for other layout prediction problems that involve tree structures and 2-dimensional placements.

Layout Design

Automatic Business Process Structure Discovery using Ordered Neurons LSTM: A Preliminary Study

no code implementations5 Jan 2020 Xue Han, Lianxue Hu, Yabin Dang, Shivali Agarwal, Lijun Mei, Shaochun Li, Xin Zhou

Automatic process discovery from textual process documentations is highly desirable to reduce time and cost of Business Process Management (BPM) implementation in organizations.

Language Modelling Management

A Survey of Predictive Maintenance: Systems, Purposes and Approaches

no code implementations12 Dec 2019 Yongyi Ran, Xin Zhou, Pengfeng Lin, Yonggang Wen, Ruilong Deng

This paper provides a comprehensive literature review on Predictive Maintenance (PdM) with emphasis on system architectures, purposes and approaches.

Model Architecture Controls Gradient Descent Dynamics: A Combinatorial Path-Based Formula

no code implementations25 Sep 2019 Xin Zhou, Newsha Ardalani

However, our theoretical understanding of how model architecture affects performance or accuracy is limited.

Intelligent Trainer for Model-Based Reinforcement Learning

1 code implementation24 May 2018 Yuanlong Li, Linsen Dong, Xin Zhou, Yonggang Wen, Kyle Guan

Model-based reinforcement learning (MBRL) has been proposed as a promising alternative solution to tackle the high sampling cost challenge in the canonical reinforcement learning (RL), by leveraging a learned model to generate synthesized data for policy training purpose.

Model-based Reinforcement Learning OpenAI Gym +2

Alibaba at IJCNLP-2017 Task 2: A Boosted Deep System for Dimensional Sentiment Analysis of Chinese Phrases

no code implementations IJCNLP 2017 Xin Zhou, Jian Wang, Xu Xie, Changlong Sun, Luo Si

For word level task our best run achieved MAE 0. 545 (ranked 2nd), PCC 0. 892 (ranked 2nd) in valence prediction and MAE 0. 857 (ranked 1st), PCC 0. 678 (ranked 2nd) in arousal prediction.

Clustering Feature Engineering +3

Causal nearest neighbor rules for optimal treatment regimes

no code implementations22 Nov 2017 Xin Zhou, Michael R. Kosorok

In this work, we propose a causal $k$-nearest neighbor method to estimate the optimal treatment regime.

Causal Inference Variable Selection

A Continuous Opinion Dynamic Model in Co-evolving Networks--A Novel Group Decision Approach

no code implementations17 May 2017 Qingxing Dong, Xin Zhou

In contrast to the traditional consensus oriented group decision making (GDM) framework, this paper proposes a framework with the co-evolution of both opinions and relationship networks to improve the potential consensus level of a group and help the group reach a stable state.

Decision Making

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