Search Results for author: Ye Liu

Found 80 papers, 27 papers with code

kNN-ICL: Compositional Task-Oriented Parsing Generalization with Nearest Neighbor In-Context Learning

no code implementations17 Dec 2023 Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Qingyang Wu, Zhongfen Deng, Jiangshu Du, Shuaiqi Liu, Yunlong Xu, Philip S. Yu

Task-Oriented Parsing (TOP) enables conversational assistants to interpret user commands expressed in natural language, transforming them into structured outputs that combine elements of both natural language and intent/slot tags.

In-Context Learning Prompt Engineering +1

DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text

no code implementations31 Oct 2023 Wenting Zhao, Ye Liu, Tong Niu, Yao Wan, Philip S. Yu, Shafiq Joty, Yingbo Zhou, Semih Yavuz

Moreover, a significant gap in the current landscape is the absence of a realistic benchmark for evaluating the effectiveness of grounding LLMs on heterogeneous knowledge sources (e. g., knowledge base and text).

Knowledge Graphs Open-Domain Question Answering +2

CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU Tasks

1 code implementation23 Oct 2023 Hoang H. Nguyen, Ye Liu, Chenwei Zhang, Tao Zhang, Philip S. Yu

While Chain-of-Thought prompting is popular in reasoning tasks, its application to Large Language Models (LLMs) in Natural Language Understanding (NLU) is under-explored.

Natural Language Understanding

VKIE: The Application of Key Information Extraction on Video Text

no code implementations18 Oct 2023 Siyu An, Ye Liu, Haoyuan Peng, Di Yin

Extracting structured information from videos is critical for numerous downstream applications in the industry.

Key Information Extraction

L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models

no code implementations29 Sep 2023 Ansong Ni, Pengcheng Yin, Yilun Zhao, Martin Riddell, Troy Feng, Rui Shen, Stephen Yin, Ye Liu, Semih Yavuz, Caiming Xiong, Shafiq Joty, Yingbo Zhou, Dragomir Radev, Arman Cohan

Recently, large language models (LLMs), especially those that are pretrained on code, have demonstrated strong capabilities in generating programs from natural language inputs in a few-shot or even zero-shot manner.

Code Generation Math +1

Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation

1 code implementation ICCV 2023 Yijun Yang, Angelica I. Aviles-Rivero, Huazhu Fu, Ye Liu, Weiming Wang, Lei Zhu

In this work, we propose the first framework for restoring videos from all adverse weather conditions by developing a video adverse-weather-component suppression network (ViWS-Net).

FedJudge: Federated Legal Large Language Model

1 code implementation15 Sep 2023 Linan Yue, Qi Liu, Yichao Du, Weibo Gao, Ye Liu, Fangzhou Yao

To this end, in this paper, we propose the first Federated Legal Large Language Model (FedJudge) framework, which fine-tunes Legal LLMs efficiently and effectively.

Continual Learning Federated Learning +2

Investigating Answerability of LLMs for Long-Form Question Answering

no code implementations15 Sep 2023 Meghana Moorthy Bhat, Rui Meng, Ye Liu, Yingbo Zhou, Semih Yavuz

As we embark on a new era of LLMs, it becomes increasingly crucial to understand their capabilities, limitations, and differences.

Long Form Question Answering Question Generation +1

XGen-7B Technical Report

1 code implementation7 Sep 2023 Erik Nijkamp, Tian Xie, Hiroaki Hayashi, Bo Pang, Congying Xia, Chen Xing, Jesse Vig, Semih Yavuz, Philippe Laban, Ben Krause, Senthil Purushwalkam, Tong Niu, Wojciech Kryściński, Lidiya Murakhovs'ka, Prafulla Kumar Choubey, Alex Fabbri, Ye Liu, Rui Meng, Lifu Tu, Meghana Bhat, Chien-Sheng Wu, Silvio Savarese, Yingbo Zhou, Shafiq Joty, Caiming Xiong

Most open-source LLMs, on the other hand, are limited in their ability to support longer sequence lengths, which is a key requirement for many tasks that require inference over an input context.

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

1 code implementation24 Aug 2023 Fei Wang, Liang Ding, Jun Rao, Ye Liu, Li Shen, Changxing Ding

The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic.

Attribute Negation +1

Exploring the Integration Strategies of Retriever and Large Language Models

no code implementations24 Aug 2023 Ye Liu, Semih Yavuz, Rui Meng, Meghana Moorthy, Shafiq Joty, Caiming Xiong, Yingbo Zhou

This paper aims to fill this gap by investigating different methods of combining retrieved passages with LLMs to enhance answer generation.

Answer Generation Open-Domain Question Answering

Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive Learning

1 code implementation9 Aug 2023 Hoang H. Nguyen, Chenwei Zhang, Ye Liu, Philip S. Yu

Recent advanced methods in Natural Language Understanding for Task-oriented Dialogue (TOD) Systems (e. g., intent detection and slot filling) require a large amount of annotated data to achieve competitive performance.

Contrastive Learning Intent Detection +5

System-Initiated Transitions from Chit-Chat to Task-Oriented Dialogues with Transition Info Extractor and Transition Sentence Generator

no code implementations6 Aug 2023 Ye Liu, Stefan Ultes, Wolfgang Minker, Wolfgang Maier

In this work, we study dialogue scenarios that start from chit-chat but eventually switch to task-related services, and investigate how a unified dialogue model, which can engage in both chit-chat and task-oriented dialogues, takes the initiative during the dialogue mode transition from chit-chat to task-oriented in a coherent and cooperative manner.

Response Generation Sentence

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI

1 code implementation19 Jul 2023 JianGuo Zhang, Kun Qian, Zhiwei Liu, Shelby Heinecke, Rui Meng, Ye Liu, Zhou Yu, Huan Wang, Silvio Savarese, Caiming Xiong

Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversity and comprehensiveness.

Few-Shot Learning Language Modelling +1

Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets

no code implementations13 Jul 2023 Amandeep Singh, Ye Liu, Hema Yoganarasimhan

We demonstrate how non-parametric estimators like neural nets can easily approximate such functionals and overcome the curse of dimensionality that is inherent in the non-parametric estimation of choice functions.

Marketing valid

Unified Conversational Models with System-Initiated Transitions between Chit-Chat and Task-Oriented Dialogues

no code implementations4 Jul 2023 Ye Liu, Stefan Ultes, Wolfgang Minker, Wolfgang Maier

We contribute two efficient prompt models which can proactively generate a transition sentence to trigger system-initiated transitions in a unified dialogue model.

Sentence Spoken Dialogue Systems

LMs: Understanding Code Syntax and Semantics for Code Analysis

no code implementations20 May 2023 Wei Ma, Shangqing Liu, ZhiHao Lin, Wenhan Wang, Qiang Hu, Ye Liu, Cen Zhang, Liming Nie, Li Li, Yang Liu

We break down the abilities needed for artificial intelligence~(AI) models to address SE tasks related to code analysis into three categories: 1) syntax understanding, 2) static behavior understanding, and 3) dynamic behavior understanding.

HPE:Answering Complex Questions over Text by Hybrid Question Parsing and Execution

no code implementations12 May 2023 Ye Liu, Semih Yavuz, Rui Meng, Dragomir Radev, Caiming Xiong, Yingbo Zhou

It comprises two central pillars: (1) We parse the question of varying complexity into an intermediate representation, named H-expression, which is composed of simple questions as the primitives and symbolic operations representing the relationships among them; (2) To execute the resulting H-expressions, we design a hybrid executor, which integrates the deterministic rules to translate the symbolic operations with a drop-in neural reader network to answer each decomposed simple question.

Knowledge Graphs Question Answering +1

Timestamps as Prompts for Geography-Aware Location Recommendation

no code implementations9 Apr 2023 Yan Luo, Haoyi Duan, Ye Liu, Fu-Lai Chung

In this paper, we revisit the problem of location recommendation and point out that explicitly modeling temporal information is a great help when the model needs to predict not only the next location but also further locations.

End-to-End Personalized Next Location Recommendation via Contrastive User Preference Modeling

no code implementations22 Mar 2023 Yan Luo, Ye Liu, Fu-Lai Chung, Yu Liu, Chang Wen Chen

History encoder is designed to model mobility patterns from historical check-in sequences, while query generator explicitly learns user preferences to generate user-specific intention queries.

Just Noticeable Visual Redundancy Forecasting: A Deep Multimodal-driven Approach

no code implementations18 Mar 2023 Wuyuan Xie, Shukang Wang, Sukun Tian, Lirong Huang, Ye Liu, Miaohui Wang

Just noticeable difference (JND) refers to the maximum visual change that human eyes cannot perceive, and it has a wide range of applications in multimedia systems.

Locating the Sources of Sub-synchronous Oscillations Induced by the Control of Voltage Source Converters Based on Energy Structure and Nonlinearity Detection

no code implementations11 Feb 2023 Zetian Zheng, Shaowei Huang, Jun Yan, Qiangsheng Bu, Chen Shen, Mingzhong Zheng, Ye Liu

The oscillation phenomena associated with the control of voltage source converters (VSCs) are widely concerning, and locating the source of these oscillations is crucial to suppressing them; therefore, this paper presents a locating scheme, based on the energy structure and nonlinearity detection.

OSAN: A One-Stage Alignment Network To Unify Multimodal Alignment and Unsupervised Domain Adaptation

no code implementations CVPR 2023 Ye Liu, Lingfeng Qiao, Changchong Lu, Di Yin, Chen Lin, Haoyuan Peng, Bo Ren

An intuitive way to handle these two problems is to fulfill these tasks in two separate stages: aligning modalities followed by domain adaptation, or vice versa.

Unsupervised Domain Adaptation

Deep Hashing With Minimal-Distance-Separated Hash Centers

no code implementations CVPR 2023 Liangdao Wang, Yan Pan, Cong Liu, Hanjiang Lai, Jian Yin, Ye Liu

This paper presents an optimization method that finds hash centers with a constraint on the minimal distance between any pair of hash centers, which is non-trivial due to the non-convex nature of the problem.

Deep Hashing Image Retrieval +1

Discrete Point-wise Attack Is Not Enough: Generalized Manifold Adversarial Attack for Face Recognition

1 code implementation CVPR 2023 Qian Li, Yuxiao Hu, Ye Liu, Dongxiao Zhang, Xin Jin, Yuntian Chen

Classical adversarial attacks for Face Recognition (FR) models typically generate discrete examples for target identity with a single state image.

Adversarial Attack Data Augmentation +1

AugTriever: Unsupervised Dense Retrieval by Scalable Data Augmentation

no code implementations17 Dec 2022 Rui Meng, Ye Liu, Semih Yavuz, Divyansh Agarwal, Lifu Tu, Ning Yu, JianGuo Zhang, Meghana Bhat, Yingbo Zhou

Dense retrievers have made significant strides in text retrieval and open-domain question answering, even though most achievements were made possible only with large amounts of human supervision.

Data Augmentation Open-Domain Question Answering +2

Equivalent Inertia Provided by Droop Control of Fast Frequency Regulation Resources

no code implementations1 Dec 2022 Ye Liu, Chen Shen

First, an equivalent-scenario-based method is proposed to evaluate the equivalent inertia provided by the droop control, which shows that the droop control with a constant droop coefficient provides time-variant equivalent inertia.

A Dynamic Equivalent Method for PMSG-WTG Based Wind Farms Considering wind Speeds and Fault Severities

no code implementations23 Nov 2022 Dongsheng Li, Chen Shen, Ye Liu, Ying Chen, Shaowei Huang

In order to reduce the complexity of simulation of power systems including large-scale wind farms, it is critical to develop dynamic equivalent methods for wind farms which are applicable to the expected contingency analysis.


Grafting Pre-trained Models for Multimodal Headline Generation

no code implementations14 Nov 2022 Lingfeng Qiao, Chen Wu, Ye Liu, Haoyuan Peng, Di Yin, Bo Ren

In this paper, we propose a novel approach to graft the video encoder from the pre-trained video-language model on the generative pre-trained language model.

Headline Generation Language Modelling +1

Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Database

no code implementations9 Nov 2022 Ye Liu, Semih Yavuz, Rui Meng, Dragomir Radev, Caiming Xiong, Yingbo Zhou

Parsing natural language questions into executable logical forms is a useful and interpretable way to perform question answering on structured data such as knowledge bases (KB) or databases (DB).

Question Answering Semantic Parsing

Unsupervised Extractive Summarization with Heterogeneous Graph Embeddings for Chinese Document

no code implementations9 Nov 2022 Chen Lin, Ye Liu, Siyu An, Di Yin

In the scenario of unsupervised extractive summarization, learning high-quality sentence representations is essential to select salient sentences from the input document.

Extractive Summarization Sentence +2

Data-driven Emergency Frequency Control for Multi-Infeed Hybrid AC-DC System

no code implementations6 Nov 2022 Qianni Cao, Ye Liu, Chen Shen

This paper develops a fully data-driven linear quadratic regulator (LQR) for the HVDC to provide temporal frequency support.

Distributed Emergency Frequency Control Considering Transient Stability Constraints in Multi-Infeed Hybrid AC-DC System

no code implementations14 Oct 2022 Ye Liu, Chen Shen, Zhaojian Wang

Both of these two control laws can guarantee transient stability constraints, restore system frequency and achieve the defined optimal control objective.

ConceptNet infused DialoGPT for Underlying Commonsense Understanding and Reasoning in Dialogue Response Generation

no code implementations29 Sep 2022 Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes

The pre-trained conversational models still fail to capture the implicit commonsense (CS) knowledge hidden in the dialogue interaction, even though they were pre-trained with an enormous dataset.

Response Generation Sentence

OS-MSL: One Stage Multimodal Sequential Link Framework for Scene Segmentation and Classification

no code implementations4 Jul 2022 Ye Liu, Lingfeng Qiao, Di Yin, Zhuoxuan Jiang, Xinghua Jiang, Deqiang Jiang, Bo Ren

In this paper, from an alternate perspective to overcome the above challenges, we unite these two tasks into one task by a new form of predicting shots link: a link connects two adjacent shots, indicating that they belong to the same scene or category.

Scene Segmentation

Contrastive Graph Multimodal Model for Text Classification in Videos

no code implementations6 Jun 2022 Ye Liu, Changchong Lu, Chen Lin, Di Yin, Bo Ren

However, to our knowledge, there is no existing work focused on the second step of video text classification, which will limit the guidance to downstream tasks such as video indexing and browsing.

Contrastive Learning Optical Character Recognition (OCR) +2

Incentive Mechanism Design for Emergency Frequency Control in Multi-Infeed Hybrid AC-DC System

no code implementations28 May 2022 Ye Liu, Chen Shen, Zhaojian Wang, Feng Liu

In multi-infeed hybrid AC-DC (MIDC) systems, the emergency frequency control (EFC) with LCC-HVDC systems participating is of vital importance for system frequency stability.

UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection

1 code implementation CVPR 2022 Ye Liu, Siyuan Li, Yang Wu, Chang Wen Chen, Ying Shan, XiaoHu Qie

Finding relevant moments and highlights in videos according to natural language queries is a natural and highly valuable common need in the current video content explosion era.

Highlight Detection Moment Retrieval +3

Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack

1 code implementation CVPR 2022 Ye Liu, Yaya Cheng, Lianli Gao, Xianglong Liu, Qilong Zhang, Jingkuan Song

Specifically, by observing that adversarial examples to a specific defense model follow some regularities in their starting points, we design an Adaptive Direction Initialization strategy to speed up the evaluation.

Adversarial Robustness

Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks

no code implementations8 Mar 2022 Jibing Gong, Yao Wan, Ye Liu, Xuewen Li, Yi Zhao, Cheng Wang, YuTing Lin, Xiaohan Fang, Wenzheng Feng, Jingyi Zhang, Jie Tang

Despite the usefulness of this service, we consider that recommending courses to users directly may neglect their varying degrees of expertise.

Graph Attention reinforcement-learning +1

Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots

1 code implementation Findings (EMNLP) 2021 Wenting Zhao, Ye Liu, Yao Wan, Philip S. Yu

Few-shot table-to-text generation is a task of composing fluent and faithful sentences to convey table content using limited data.

Table-to-Text Generation

Context Matters in Semantically Controlled Language Generation for Task-oriented Dialogue Systems

no code implementations ICON 2021 Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes

We utilize the pre-trained multi-context ConveRT model for context representation in a model trained from scratch; and leverage the immediate preceding user utterance for context generation in a model adapted from the pre-trained GPT-2.

Response Generation Task-Oriented Dialogue Systems +1

Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images

1 code implementation22 Nov 2021 Ye Liu, Huifang Li, Chao Hu, Shuang Luo, Yan Luo, Chang Wen Chen

The proposed model exploits three lightweight plug-and-play modules, namely dense feature pyramid network (DenseFPN), spatial context pyramid (SCP), and hierarchical region of interest extractor (HRoIE), to aggregate global visual context at feature, spatial, and instance domains, respectively.

Instance Segmentation Object Detection

A Probit Tensor Factorization Model For Relational Learning

no code implementations6 Nov 2021 Ye Liu, Rui Song, Wenbin Lu, Yanghua Xiao

A large number of models and algorithms have been proposed to perform link prediction, among which tensor factorization method has proven to achieve state-of-the-art performance in terms of computation efficiency and prediction accuracy.

Knowledge Graphs Link Prediction +1

Dense Hierarchical Retrieval for Open-Domain Question Answering

1 code implementation Findings (EMNLP) 2021 Ye Liu, Kazuma Hashimoto, Yingbo Zhou, Semih Yavuz, Caiming Xiong, Philip S. Yu

In this work, we propose Dense Hierarchical Retrieval (DHR), a hierarchical framework that can generate accurate dense representations of passages by utilizing both macroscopic semantics in the document and microscopic semantics specific to each passage.

Open-Domain Question Answering Retrieval +1

Empathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge

no code implementations7 Sep 2021 Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes

One challenge for dialogue agents is to recognize feelings of the conversation partner and respond accordingly.

Dialogue Generation

From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data

1 code implementation6 Aug 2021 Ye Liu, Lei Zhu, Shunda Pei, Huazhu Fu, Jing Qin, Qing Zhang, Liang Wan, Wei Feng

Our DID-Net predicts the three component maps by progressively integrating features across scales, and refines each map by passing an independent refinement network.

Image Dehazing Single Image Dehazing

Enriching Non-Autoregressive Transformer with Syntactic and Semantic Structures for Neural Machine Translation

no code implementations EACL 2021 Ye Liu, Yao Wan, JianGuo Zhang, Wenting Zhao, Philip Yu

In this paper, we claim that the syntactic and semantic structures among natural language are critical for non-autoregressive machine translation and can further improve the performance.

Machine Translation Translation

Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation

no code implementations22 Jan 2021 Ye Liu, Yao Wan, Jian-Guo Zhang, Wenting Zhao, Philip S. Yu

In this paper, we claim that the syntactic and semantic structures among natural language are critical for non-autoregressive machine translation and can further improve the performance.

Machine Translation Translation

Real-Time Vanishing Point Detector Integrating Under-Parameterized RANSAC and Hough Transform

no code implementations ICCV 2021 Jianping Wu, Liang Zhang, Ye Liu, Ke Chen

We propose a novel approach that integrates under-parameterized RANSAC (UPRANSAC) with Hough Transform to detect vanishing points (VPs) from un-calibrated monocular images.

KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning

1 code implementation26 Sep 2020 Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu

To promote the ability of commonsense reasoning for text generation, we propose a novel knowledge graph augmented pre-trained language generation model KG-BART, which encompasses the complex relations of concepts through the knowledge graph and produces more logical and natural sentences as output.

Graph Attention Text Generation

ConsNet: Learning Consistency Graph for Zero-Shot Human-Object Interaction Detection

2 code implementations14 Aug 2020 Ye Liu, Junsong Yuan, Chang Wen Chen

We consider the problem of Human-Object Interaction (HOI) Detection, which aims to locate and recognize HOI instances in the form of <human, action, object> in images.

Human-Object Interaction Detection Object +1

Interpretable Multi-Step Reasoning with Knowledge Extraction on Complex Healthcare Question Answering

no code implementations6 Aug 2020 Ye Liu, Shaika Chowdhury, Chenwei Zhang, Cornelia Caragea, Philip S. Yu

Unlike most other QA tasks that focus on linguistic understanding, HeadQA requires deeper reasoning involving not only knowledge extraction, but also complex reasoning with healthcare knowledge.

Multiple-choice Question Answering

Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics

1 code implementation28 Feb 2020 Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S. Rosenblum

This framework consists of three parts: 1) a local feature extraction module to learn representations for each region; 2) a global context module to extract global contextual priors and upsample them to generate the global features; and 3) a region-specific predictor based on tensor decomposition to provide customized predictions for each region, which is very parameter-efficient compared to previous methods.

Tensor Decomposition

Fine-Grained Urban Flow Inference

1 code implementation5 Feb 2020 Kun Ouyang, Yuxuan Liang, Ye Liu, Zekun Tong, Sijie Ruan, Yu Zheng, David S. Rosenblum

To tackle these issues, we develop a model entitled UrbanFM which consists of two major parts: 1) an inference network to generate fine-grained flow distributions from coarse-grained inputs that uses a feature extraction module and a novel distributional upsampling module; 2) a general fusion subnet to further boost the performance by considering the influence of different external factors.

Fine-Grained Urban Flow Inference

Orthogonal Nonnegative Tucker Decomposition

no code implementations21 Oct 2019 Junjun Pan, Michael K. Ng, Ye Liu, Xiongjun Zhang, Hong Yan

In this paper, we study the nonnegative tensor data and propose an orthogonal nonnegative Tucker decomposition (ONTD).

Face Recognition Hyperspectral Unmixing

Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System

1 code implementation13 Aug 2019 Ye Liu, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu

To improve the quality and retrieval performance of the generated questions, we make two major improvements: 1) To better encode the semantics of ill-formed questions, we enrich the representation of questions with character embedding and the recent proposed contextual word embedding such as BERT, besides the traditional context-free word embeddings; 2) To make it capable to generate desired questions, we train the model with deep reinforcement learning techniques that considers an appropriate wording of the generation as an immediate reward and the correlation between generated question and answer as time-delayed long-term rewards.

Question Answering reinforcement-learning +3

Tucker Decomposition Network: Expressive Power and Comparison

no code implementations23 May 2019 Ye Liu, Junjun Pan, Michael Ng

Deep neural networks have achieved a great success in solving many machine learning and computer vision problems.

General Classification Image Classification +1

MMKG: Multi-Modal Knowledge Graphs

5 code implementations13 Mar 2019 Ye Liu, Hui Li, Alberto Garcia-Duran, Mathias Niepert, Daniel Onoro-Rubio, David S. Rosenblum

We present MMKG, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs.

Knowledge Graphs Link Prediction

UrbanFM: Inferring Fine-Grained Urban Flows

1 code implementation6 Feb 2019 Yuxuan Liang, Kun Ouyang, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S. Rosenblum, Yu Zheng

In this paper, we aim to infer the real-time and fine-grained crowd flows throughout a city based on coarse-grained observations.

Fine-Grained Urban Flow Inference

Automatic trajectory measurement of large numbers of crowded objects

no code implementations3 Feb 2019 Hui Li, Ye Liu, Yan Qiu Chen

Complex motion patterns of natural systems, such as fish schools, bird flocks, and cell groups, have attracted great attention from scientists for years.

Data-driven Blockbuster Planning on Online Movie Knowledge Library

no code implementations24 Oct 2018 Ye Liu, Jiawei Zhang, Chenwei Zhang, Philip S. Yu

After a thorough investigation of an online movie knowledge library, a novel movie planning framework "Blockbuster Planning with Maximized Movie Configuration Acquaintance" (BigMovie) is introduced in this paper.

ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection

no code implementations11 Jul 2018 Bo Jiang, Ye Liu, W. K. Chan

Decentralized cryptocurrencies feature the use of blockchain to transfer values among peers on networks without central agency.

Software Engineering Cryptography and Security

Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis

no code implementations19 Jun 2018 Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow

Network analysis of human brain connectivity is critically important for understanding brain function and disease states.

Clustering Graph Embedding

Beyond Binary Labels: Political Ideology Prediction of Twitter Users

no code implementations ACL 2017 Daniel Preo{\c{t}}iuc-Pietro, Ye Liu, Daniel Hopkins, Lyle Ungar

Automatic political orientation prediction from social media posts has to date proven successful only in distinguishing between publicly declared liberals and conservatives in the US.

Action2Activity: Recognizing Complex Activities from Sensor Data

no code implementations7 Nov 2016 Ye Liu, Liqiang Nie, Lei Han, Luming Zhang, David S. Rosenblum

As compared to simple actions, activities are much more complex, but semantically consistent with a human's real life.

Action Recognition Multi-Task Learning +1

Simultaneous Feature Learning and Hash Coding with Deep Neural Networks

no code implementations CVPR 2015 Hanjiang Lai, Yan Pan, Ye Liu, Shuicheng Yan

Similarity-preserving hashing is a widely-used method for nearest neighbour search in large-scale image retrieval tasks.

Image Retrieval Quantization +1

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