Search Results for author: Yue Hu

Found 88 papers, 39 papers with code

基于Graph Transformer的知识库问题生成(Question Generation from Knowledge Base with Graph Transformer)

no code implementations CCL 2020 Yue Hu, Guangyou Zhou

知识库问答依靠知识库推断答案需大量带标注信息的问答对, 但构建大规模且精准的数据集不仅代价昂贵, 还受领域等因素限制。为缓解数据标注问题, 面向知识库的问题生成任务引起了研究者关注, 该任务是利用知识库三元组自动生成问题。现有方法仅由一个三元组生成的问题简短且缺乏多样性。为生成信息量丰富且多样化的问题, 本文采用Graph Transformer和BERT两个编码层来加强三元组多粒度语义表征以获取背景信息。在SimpleQuestions上的实验结果证明了该方法有效性。

Question Generation Question-Generation

Comparison of the effects of attention mechanism on translation tasks of different lengths of ambiguous words

no code implementations AACL (iwdp) 2020 Yue Hu, Jiahao Qin, Zemeiqi Chen, Jingshi Zhou, Xiaojun Zhang

This paper focuses on the performance of encoder decoder attention mechanism in word sense disambiguation task with different text length, trying to find out the influence of context marker on attention mechanism in word sense disambiguation task.

Decoder Machine Translation +3

AtomGS: Atomizing Gaussian Splatting for High-Fidelity Radiance Field

no code implementations20 May 2024 Rong Liu, Rui Xu, Yue Hu, Meida Chen, Andrew Feng

3D Gaussian Splatting (3DGS) has recently advanced radiance field reconstruction by offering superior capabilities for novel view synthesis and real-time rendering speed.

Novel View Synthesis

DARA: Domain- and Relation-aware Adapters Make Parameter-efficient Tuning for Visual Grounding

1 code implementation10 May 2024 Ting Liu, Xuyang Liu, Siteng Huang, Honggang Chen, Quanjun Yin, Long Qin, Donglin Wang, Yue Hu

Specifically, we propose \textbf{DARA}, a novel PETL method comprising \underline{\textbf{D}}omain-aware \underline{\textbf{A}}dapters (DA Adapters) and \underline{\textbf{R}}elation-aware \underline{\textbf{A}}dapters (RA Adapters) for VG.

Relation Transfer Learning +1

Detection of circular permutations by Protein Language Models

1 code implementation23 Apr 2024 Yue Hu, Bin Huang

The protein language model can help us extract structural information from sequences.

Protein Language Model

Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System

1 code implementation15 Apr 2024 Genjia Liu, Yue Hu, Chenxin Xu, Weibo Mao, Junhao Ge, Zhengxiang Huang, Yifan Lu, Yinda Xu, Junkai Xia, Yafei Wang, Siheng Chen

This effort necessitates two key foundations: a platform capable of generating data to facilitate the training and testing of V2X-AD, and a comprehensive system that integrates full driving-related functionalities with mechanisms for information sharing.

Autonomous Driving

An Extensible Framework for Open Heterogeneous Collaborative Perception

1 code implementation25 Jan 2024 Yifan Lu, Yue Hu, Yiqi Zhong, Dequan Wang, Yanfeng Wang, Siheng Chen

In this paper, we introduce a new open heterogeneous problem: how to accommodate continually emerging new heterogeneous agent types into collaborative perception, while ensuring high perception performance and low integration cost?

Pragmatic Communication in Multi-Agent Collaborative Perception

no code implementations23 Jan 2024 Yue Hu, Xianghe Pang, Xiaoqi Qin, Yonina C. Eldar, Siheng Chen, Ping Zhang, Wenjun Zhang

Following this strategy, we first formulate a mathematical optimization framework for the perception-communication trade-off and then propose PragComm, a multi-agent collaborative perception system with two key components: i) single-agent detection and tracking and ii) pragmatic collaboration.

3D Object Detection object-detection

Helping Language Models Learn More: Multi-dimensional Task Prompt for Few-shot Tuning

no code implementations13 Dec 2023 Jinta Weng, Jiarui Zhang, Yue Hu, Daidong Fa, Xiaofeng Xuand, Heyan Huang

In interaction with large language models, embedding more task-related information into prompts will make it easier to stimulate knowledge embedded in large language models.

Language Modelling Large Language Model +1

Watermarking Vision-Language Pre-trained Models for Multi-modal Embedding as a Service

1 code implementation10 Nov 2023 Yuanmin Tang, Jing Yu, Keke Gai, Xiangyan Qu, Yue Hu, Gang Xiong, Qi Wu

Our extensive experiments on various datasets indicate that the proposed watermarking approach is effective and safe for verifying the copyright of VLPs for multi-modal EaaS and robust against model extraction attacks.

Model extraction

S2F-NER: Exploring Sequence-to-Forest Generation for Complex Entity Recognition

no code implementations29 Oct 2023 Yongxiu Xu, Heyan Huang, Yue Hu

Named Entity Recognition (NER) remains challenging due to the complex entities, like nested, overlapping, and discontinuous entities.

Decoder named-entity-recognition +3

Exploiting Manifold Structured Data Priors for Improved MR Fingerprinting Reconstruction

no code implementations9 Oct 2023 Peng Li, Yuping Ji, Yue Hu

To fill this gap, we propose a novel MRF reconstruction framework based on manifold structured data priors.

Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored Search

1 code implementation28 Sep 2023 Yuanmin Tang, Jing Yu, Keke Gai, Yujing Wang, Yue Hu, Gang Xiong, Qi Wu

Conventional research mainly studies from the view of modeling the implicit correlations between images and texts for query-ads matching, ignoring the alignment of detailed product information and resulting in suboptimal search performance. In this work, we propose a simple alignment network for explicitly mapping fine-grained visual parts in ads images to the corresponding text, which leverages the co-occurrence structure consistency between vision and language spaces without requiring expensive labeled training data.

Image-text matching Natural Language Queries

Context-I2W: Mapping Images to Context-dependent Words for Accurate Zero-Shot Composed Image Retrieval

1 code implementation28 Sep 2023 Yuanmin Tang, Jing Yu, Keke Gai, Jiamin Zhuang, Gang Xiong, Yue Hu, Qi Wu

Different from Composed Image Retrieval task that requires expensive labels for training task-specific models, Zero-Shot Composed Image Retrieval (ZS-CIR) involves diverse tasks with a broad range of visual content manipulation intent that could be related to domain, scene, object, and attribute.

Attribute Image Retrieval +4

Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types

no code implementations15 Sep 2023 Yue Hu, Gourav Datta, Kira Beerel, Peter Beerel

This implies that ML pipelines might not need explicit correction for RS for many object detection applications, but mitigating RS effects in ISP-less ML pipelines that target fine-grained location of the objects may need additional research.

object-detection Object Detection +1

Prompt-based Context- and Domain-aware Pretraining for Vision and Language Navigation

no code implementations7 Sep 2023 Ting Liu, Yue Hu, Wansen Wu, Youkai Wang, Kai Xu, Quanjun Yin

In the indoor-aware stage, we apply an efficient tuning paradigm to learn deep visual prompts from an indoor dataset, in order to augment pretrained models with inductive biases towards indoor environments.

Contrastive Learning Vision and Language Navigation +1

Towards Fast and Accurate Image-Text Retrieval with Self-Supervised Fine-Grained Alignment

1 code implementation27 Aug 2023 Jiamin Zhuang, Jing Yu, Yang Ding, Xiangyan Qu, Yue Hu

Image-text retrieval requires the system to bridge the heterogenous gap between vision and language for accurate retrieval while keeping the network lightweight-enough for efficient retrieval.

Contrastive Learning Retrieval +1

FireFly A Synthetic Dataset for Ember Detection in Wildfire

1 code implementation6 Aug 2023 Yue Hu, Xinan Ye, Yifei Liu, Souvik Kundu, Gourav Datta, Srikar Mutnuri, Namo Asavisanu, Nora Ayanian, Konstantinos Psounis, Peter Beerel

This paper presents "FireFly", a synthetic dataset for ember detection created using Unreal Engine 4 (UE4), designed to overcome the current lack of ember-specific training resources.

object-detection Object Detection

Deep unrolling Shrinkage Network for Dynamic MR imaging

1 code implementation19 Jul 2023 Yinghao Zhang, Xiaodi Li, Weihang Li, Yue Hu

In particular, we put forward a novel deep unrolling shrinkage network (DUS-Net) by unrolling the alternating direction method of multipliers (ADMM) for optimizing the transformed $l_1$ norm dynamic MR reconstruction model.

Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks

1 code implementation23 Apr 2023 Yue Hu, Yuhang Zhang, Yanbing Wang, Daniel Work

In this work, we consider the problem of detecting a variety of socially abnormal driving behaviors, i. e., behaviors that do not conform to the behavior of other nearby drivers.

Anomaly Detection Graph Attention

Category Query Learning for Human-Object Interaction Classification

1 code implementation CVPR 2023 Chi Xie, Fangao Zeng, Yue Hu, Shuang Liang, Yichen Wei

Unlike most previous HOI methods that focus on learning better human-object features, we propose a novel and complementary approach called category query learning.

Classification Decoder +3

Collaboration Helps Camera Overtake LiDAR in 3D Detection

1 code implementation CVPR 2023 Yue Hu, Yifan Lu, Runsheng Xu, Weidi Xie, Siheng Chen, Yanfeng Wang

Camera-only 3D detection provides an economical solution with a simple configuration for localizing objects in 3D space compared to LiDAR-based detection systems.

Depth Estimation

Subspace based Federated Unlearning

no code implementations24 Feb 2023 Guanghao Li, Li Shen, Yan Sun, Yue Hu, Han Hu, DaCheng Tao

Federated learning (FL) enables multiple clients to train a machine learning model collaboratively without exchanging their local data.

Federated Learning

FADO: Feedback-Aware Double COntrolling Network for Emotional Support Conversation

no code implementations1 Nov 2022 Wei Peng, Ziyuan Qin, Yue Hu, Yuqiang Xie, Yunpeng Li

The core module in FADO consists of a dual-level feedback strategy selector and a double control reader.

Response Generation

Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation

no code implementations18 Oct 2022 Yangheng Zhao, Jun Wang, Xiaolong Li, Yue Hu, Ce Zhang, Yanfeng Wang, Siheng Chen

Instead of learning a single prototype for each class, in this paper, we propose to use an adaptive number of prototypes to dynamically describe the different point patterns within a semantic class.

3D Semantic Segmentation Scene Understanding +1

Psychology-guided Controllable Story Generation

no code implementations COLING 2022 Yuqiang Xie, Yue Hu, Yunpeng Li, Guanqun Bi, Luxi Xing, Wei Peng

Inspired by psychology theories, we introduce global psychological state chains, which include the needs and emotions of the protagonists, to help a story generation system create more controllable and well-planned stories.

Story Generation

Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps

2 code implementations26 Sep 2022 Yue Hu, Shaoheng Fang, Zixing Lei, Yiqi Zhong, Siheng Chen

Where2comm has two distinct advantages: i) it considers pragmatic compression and uses less communication to achieve higher perception performance by focusing on perceptually critical areas; and ii) it can handle varying communication bandwidth by dynamically adjusting spatial areas involved in communication.

Monocular 3D Object Detection object-detection

Learning Reconstructability for Drone Aerial Path Planning

no code implementations21 Sep 2022 Yilin Liu, Liqiang Lin, Yue Hu, Ke Xie, Chi-Wing Fu, Hao Zhang, Hui Huang

To reconstruct a new urban scene, we first build the 3D scene proxy, then rely on the predicted reconstruction quality and uncertainty measures by our network, based off of the proxy geometry, to guide the drone path planning.

3D Scene Reconstruction

T$^2$LR-Net: An Unrolling Reconstruction Network Learning Transformed Tensor Low-Rank prior for Dynamic MR Imaging

1 code implementation8 Sep 2022 Yinghao Zhang, Yue Hu

By generalizing the FFT into an arbitrary unitary transformation of the transformed t-SVD and proposing the transformed tensor nuclear norm (TTNN), we introduce a flexible model based on TTNN with the ability to exploit the tensor low-rank prior of a transformed domain in a larger transformation space and elaborately design an iterative optimization algorithm based on the alternating direction method of multipliers (ADMM), which is further unrolled into a model-based deep unrolling reconstruction network to learn the transformed tensor low-rank prior (T$^2$LR-Net).

Image Reconstruction Rolling Shutter Correction

Multi-level Contrastive Learning Framework for Sequential Recommendation

no code implementations27 Aug 2022 Ziyang Wang, Huoyu Liu, Wei Wei, Yue Hu, Xian-Ling Mao, Shaojian He, Rui Fang, Dangyang Chen

Different from the previous contrastive learning-based methods for SR, MCLSR learns the representations of users and items through a cross-view contrastive learning paradigm from four specific views at two different levels (i. e., interest- and feature-level).

Contrastive Learning Relation +1

Neural Message Passing for Visual Relationship Detection

1 code implementation8 Aug 2022 Yue Hu, Siheng Chen, Xu Chen, Ya zhang, Xiao Gu

Visual relationship detection aims to detect the interactions between objects in an image; however, this task suffers from combinatorial explosion due to the variety of objects and interactions.

Relationship Detection Visual Relationship Detection

Aerial Monocular 3D Object Detection

no code implementations8 Aug 2022 Yue Hu, Shaoheng Fang, Weidi Xie, Siheng Chen

To fill the gap, this work proposes a dual-view detection system named DVDET to achieve aerial monocular object detection in both the 2D image space and the 3D physical space.

Autonomous Driving Monocular 3D Object Detection +2

Latency-Aware Collaborative Perception

1 code implementation18 Jul 2022 Zixing Lei, Shunli Ren, Yue Hu, Wenjun Zhang, Siheng Chen

Collaborative perception has recently shown great potential to improve perception capabilities over single-agent perception.

Autonomous Driving

Do You Know My Emotion? Emotion-Aware Strategy Recognition towards a Persuasive Dialogue System

1 code implementation24 Jun 2022 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun

Specifically, CFO-Net designs a feedback memory module, including strategy pool and feedback pool, to obtain emotion-aware strategy representation.

FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity

no code implementations21 Jun 2022 Guanghao Li, Yue Hu, Miao Zhang, Ji Liu, Quanjun Yin, Yong Peng, Dejing Dou

As the efficiency of training in the ring topology prefers devices with homogeneous resources, the classification based on the computing capacity mitigates the impact of straggler effects.

Federated Learning

Dynamic MRI using Learned Transform-based Tensor Low-Rank Network (LT$^2$LR-Net)

no code implementations2 Jun 2022 Yinghao Zhang, Peng Li, Yue Hu

While low-rank matrix prior has been exploited in dynamic MR image reconstruction and has obtained satisfying performance, tensor low-rank models have recently emerged as powerful alternative representations for three-dimensional dynamic MR datasets.

MRI Reconstruction Rolling Shutter Correction +1

Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation

1 code implementation27 Apr 2022 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, Yunpeng Li

Emotional support conversation aims at reducing the emotional distress of the help-seeker, which is a new and challenging task.

Decoder

Dir-MUSIC Algorithm for DOA Estimation of Partial Discharge Based on Signal Strength represented by Antenna Gain Array Manifold

no code implementations19 Apr 2022 Wencong Xu, Yandong Li, Bingshu Chen, Yue Hu, Jianxu Li, Zijing Zeng

The experimental results show that the PD direction-finding error is 3. 39{\deg}, which can meet the need for Partial discharge DOA estimation using inspection robots in substations.

Learning to Generalize to More: Continuous Semantic Augmentation for Neural Machine Translation

2 code implementations ACL 2022 Xiangpeng Wei, Heng Yu, Yue Hu, Rongxiang Weng, Weihua Luo, Jun Xie, Rong Jin

Although data augmentation is widely used to enrich the training data, conventional methods with discrete manipulations fail to generate diverse and faithful training samples.

Data Augmentation Machine Translation +3

MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question Answering

1 code implementation CVPR 2022 Yang Ding, Jing Yu, Bang Liu, Yue Hu, Mingxin Cui, Qi Wu

Knowledge-based visual question answering requires the ability of associating external knowledge for open-ended cross-modal scene understanding.

Implicit Relations Question Answering +2

CLSEG: Contrastive Learning of Story Ending Generation

1 code implementation18 Feb 2022 Yuqiang Xie, Yue Hu, Luxi Xing, Yunpeng Li, Wei Peng, Ping Guo

To address these two issues, we propose a novel Contrastive Learning framework for Story Ending Generation (CLSEG), which has two steps: multi-aspect sampling and story-specific contrastive learning.

Contrastive Learning Text Generation

Streaming data preprocessing via online tensor recovery for large environmental sensor networks

1 code implementation1 Sep 2021 Yue Hu, Ao Qu, Yanbing Wang, Dan Work

Measuring the built and natural environment at a fine-grained scale is now possible with low-cost urban environmental sensor networks.

Know Deeper: Knowledge-Conversation Cyclic Utilization Mechanism for Open-domain Dialogue Generation

no code implementations16 Jul 2021 Yajing Sun, Yue Hu, Luxi Xing, Yuqiang Xie, Xiangpeng Wei

End-to-End intelligent neural dialogue systems suffer from the problems of generating inconsistent and repetitive responses.

Decoder Dialogue Generation +1

Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset

2 code implementations9 Jul 2021 Liqiang Lin, Yilin Liu, Yue Hu, Xingguang Yan, Ke Xie, Hui Huang

We present UrbanScene3D, a large-scale data platform for research of urban scene perception and reconstruction.

3D Reconstruction Instance Segmentation +1

Coarse-to-Careful: Seeking Semantic-related Knowledge for Open-domain Commonsense Question Answering

no code implementations4 Jul 2021 Luxi Xing, Yue Hu, Jing Yu, Yuqiang Xie, Wei Peng

It is prevalent to utilize external knowledge to help machine answer questions that need background commonsense, which faces a problem that unlimited knowledge will transmit noisy and misleading information.

Question Answering

MCR-Net: A Multi-Step Co-Interactive Relation Network for Unanswerable Questions on Machine Reading Comprehension

no code implementations8 Mar 2021 Wei Peng, Yue Hu, Jing Yu, Luxi Xing, Yuqiang Xie, Zihao Zhu, Yajing Sun

Most of the existing systems design a simple classifier to determine answerability implicitly without explicitly modeling mutual interaction and relation between the question and passage, leading to the poor performance for determining the unanswerable questions.

Machine Reading Comprehension Question Answering +2

Revealing Gravitational Collapse in Serpens G3-G6 Molecular Cloud using Velocity Gradients

no code implementations11 Feb 2021 Yue Hu, A. Lazarian, Snezana Stanimirovic

We suggest that the Serpens G3-G6 south clump is undergoing a gravitational collapse.

Astrophysics of Galaxies

Measuring magnetization with rotation measures and velocity centroids in supersonic MHD turbulence

no code implementations10 Feb 2021 Siyao Xu, Yue Hu

The interstellar turbulence is magnetized and thus anisotropic.

Astrophysics of Galaxies

Graph Convolutional Networks for traffic anomaly

1 code implementation25 Dec 2020 Yue Hu, Ao Qu, Dan Work

Event detection has been an important task in transportation, whose task is to detect points in time when large events disrupts a large portion of the urban traffic network.

Anomaly Detection Event Detection +1

Anisotropies in Compressible MHD Turbulence: Probing Magnetic Fields and Measuring Magnetization

no code implementations11 Dec 2020 Yue Hu, Siyao Xu, A. Lazarian

We demonstrate that the anisotropic structure functions of turbulent velocities can be used to estimate both the orientation and strength of magnetic fields.

Astrophysics of Galaxies

Bi-directional CognitiveThinking Network for Machine Reading Comprehension

no code implementations COLING 2020 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Jing Yu, Yajing Sun, Xiangpeng Wei

We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory.

Machine Reading Comprehension

Learning User Representations with Hypercuboids for Recommender Systems

3 code implementations11 Nov 2020 Shuai Zhang, Huoyu Liu, Aston Zhang, Yue Hu, Ce Zhang, Yumeng Li, Tanchao Zhu, Shaojian He, Wenwu Ou

Furthermore, we present two variants of hypercuboids to enhance the capability in capturing the diversities of user interests.

Collaborative Filtering Recommendation Systems

Bi-directional Cognitive Thinking Network for Machine Reading Comprehension

no code implementations20 Oct 2020 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Jing Yu, Yajing Sun, Xiangpeng Wei

We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory.

Machine Reading Comprehension

Uncertainty-Aware Semantic Augmentation for Neural Machine Translation

no code implementations EMNLP 2020 Xiangpeng Wei, Heng Yu, Yue Hu, Rongxiang Weng, Luxi Xing, Weihua Luo

As a sequence-to-sequence generation task, neural machine translation (NMT) naturally contains intrinsic uncertainty, where a single sentence in one language has multiple valid counterparts in the other.

Machine Translation NMT +3

CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation

1 code implementation16 Sep 2020 Jing Yu, Yuan Chai, Yujing Wang, Yue Hu, Qi Wu

We first build a cognitive structure CogTree to organize the relationships based on the prediction of a biased SGG model.

Ranked #2 on Scene Graph Generation on Visual Genome (mean Recall @20 metric)

Graph Generation Unbiased Scene Graph Generation

Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering

no code implementations31 Aug 2020 Jing Yu, Zihao Zhu, Yujing Wang, Weifeng Zhang, Yue Hu, Jianlong Tan

Finally, we perform graph neural networks to infer the global-optimal answer by jointly considering all the concepts.

Knowledge Graphs Question Answering +1

Study Turbulence and Probe Magnetic Field Using Gradient Technique: Application to HI-to-H2 Transition Regions

no code implementations2 Aug 2020 Yue Hu, A. Lazarian, Shmuel Bialy

In this work, we consider the effect of turbulence on the HI and H2 transition and explore the possibility of tracing the magnetic field direction in photodissociation regions using the Gradient Technique.

Astrophysics of Galaxies

On Learning Universal Representations Across Languages

no code implementations ICLR 2021 Xiangpeng Wei, Rongxiang Weng, Yue Hu, Luxi Xing, Heng Yu, Weihua Luo

Recent studies have demonstrated the overwhelming advantage of cross-lingual pre-trained models (PTMs), such as multilingual BERT and XLM, on cross-lingual NLP tasks.

Contrastive Learning Cross-Lingual Natural Language Inference +4

DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue

4 code implementations7 Jul 2020 Xiaoze Jiang, Jing Yu, Yajing Sun, Zengchang Qin, Zihao Zhu, Yue Hu, Qi Wu

The ability of generating detailed and non-repetitive responses is crucial for the agent to achieve human-like conversation.

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering

no code implementations16 Jun 2020 Zihao Zhu, Jing Yu, Yujing Wang, Yajing Sun, Yue Hu, Qi Wu

In this paper, we depict an image by a multi-modal heterogeneous graph, which contains multiple layers of information corresponding to the visual, semantic and factual features.

Question Answering Visual Question Answering

Multiscale Collaborative Deep Models for Neural Machine Translation

1 code implementation ACL 2020 Xiangpeng Wei, Heng Yu, Yue Hu, Yue Zhang, Rongxiang Weng, Weihua Luo

Recent evidence reveals that Neural Machine Translation (NMT) models with deeper neural networks can be more effective but are difficult to train.

Machine Translation NMT +1

DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue

1 code implementation17 Nov 2019 Xiaoze Jiang, Jing Yu, Zengchang Qin, Yingying Zhuang, Xingxing Zhang, Yue Hu, Qi Wu

More importantly, we can tell which modality (visual or semantic) has more contribution in answering the current question by visualizing the gate values.

feature selection Question Answering +2

Unsupervised Neural Machine Translation with Future Rewarding

no code implementations CONLL 2019 Xiangpeng Wei, Yue Hu, Luxi Xing, Li Gao

In this paper, we alleviate the local optimality of back-translation by learning a policy (takes the form of an encoder-decoder and is defined by its parameters) with future rewarding under the reinforcement learning framework, which aims to optimize the global word predictions for unsupervised neural machine translation.

Decoder Machine Translation +4

Robust Tensor Recovery with Fiber Outliers for Traffic Events

no code implementations27 Aug 2019 Yue Hu, Dan Work

In this article, we develop a method to detect extreme events in large traffic datasets, and to impute missing data during regular conditions.

Event Detection Tensor Decomposition

Influence of Boundaries and Thermostatting on Nonequilibrium Molecular Dynamics Simulations of Heat Conduction in Solids

no code implementations27 May 2019 Zhen Li, Shiyun Xiong, Charles Sievers, Yue Hu, Zheyong Fan, Ning Wei, Hua Bao, Shunda Chen, Davide Donadio, Tapio Ala-Nissila

Conventionally, the thermal conductivity of a finite system is calculated as the ratio between the heat flux and the temperature gradient extracted from the linear part of the temperature profile away from the local thermostats.

Mesoscale and Nanoscale Physics Statistical Mechanics Computational Physics

GraphNAS: Graph Neural Architecture Search with Reinforcement Learning

1 code implementation22 Apr 2019 Yang Gao, Hong Yang, Peng Zhang, Chuan Zhou, Yue Hu

On node classification tasks, GraphNAS can design a novel network architecture that rivals the best human-invented architecture in terms of test set accuracy.

General Classification Neural Architecture Search +3

Scene Graph Reasoning with Prior Visual Relationship for Visual Question Answering

no code implementations23 Dec 2018 Zhuoqian Yang, Zengchang Qin, Jing Yu, Yue Hu

Upon the constructed graph, we propose a Scene Graph Convolutional Network (SceneGCN) to jointly reason the object properties and relational semantics for the correct answer.

Cross-Modal Information Retrieval Information Retrieval +2

Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder

no code implementations5 Nov 2018 Junjie Zeng, Long Qin, Yue Hu, Cong Hu, Quanjun Yin

The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments.

Motion Planning Optimal Motion Planning +3

Textual Relationship Modeling for Cross-Modal Information Retrieval

1 code implementation31 Oct 2018 Jing Yu, Chenghao Yang, Zengchang Qin, Zhuoqian Yang, Yue Hu, Yanbing Liu

A joint neural model is proposed to learn feature representation individually in each modality.

Multimedia

A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots

1 code implementation6 Sep 2018 Giulio Romualdi, Stefano Dafarra, Yue Hu, Daniele Pucci

More precisely, we present and compare several DCM based implementations of a three layer control architecture.

Robotics

Mining and Analyzing the Future Works in Scientific Articles

no code implementations8 Jul 2015 Yue Hu, Xiaojun Wan

Third, we apply the extraction method and the classification model to a paper dataset in the computer science field and conduct a further analysis of the future works.

Classification General Classification

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