Search Results for author: Muhao Chen

Found 84 papers, 47 papers with code

New Frontiers of Information Extraction

no code implementations NAACL (ACL) 2022 Muhao Chen, Lifu Huang, Manling Li, Ben Zhou, Heng Ji, Dan Roth

This tutorial targets researchers and practitioners who are interested in AI and ML technologies for structural information extraction (IE) from unstructured textual sources.

Robust Natural Language Understanding with Residual Attention Debiasing

1 code implementation28 May 2023 Fei Wang, James Y. Huang, Tianyi Yan, Wenxuan Zhou, Muhao Chen

However, previous ensemble-based debiasing methods typically apply debiasing on top-level logits without directly addressing biased attention patterns.

Natural Language Understanding

Adversarial Demonstration Attacks on Large Language Models

no code implementations24 May 2023 Jiongxiao Wang, Zichen Liu, Keun Hee Park, Muhao Chen, Chaowei Xiao

With the emergence of more powerful large language models (LLMs), such as ChatGPT and GPT-4, in-context learning (ICL) has gained significant prominence in leveraging these models for specific tasks by utilizing data-label pairs as precondition prompts.

Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality

1 code implementation24 May 2023 Tanay Dixit, Fei Wang, Muhao Chen

However, most of the prior works on training factuality-aware models have ignored the negative effect it has on summary quality.

Abstractive Text Summarization Contrastive Learning

A Causal View of Entity Bias in (Large) Language Models

no code implementations24 May 2023 Fei Wang, Wenjie Mo, Yiwei Wang, Wenxuan Zhou, Muhao Chen

Meanwhile, our in-context intervention effectively reduces the knowledge conflicts between parametric knowledge and contextual knowledge in GPT-3. 5 and improves the F1 score by 9. 14 points on a challenging test set derived from Re-TACRED.

Relation Extraction

How Fragile is Relation Extraction under Entity Replacements?

1 code implementation22 May 2023 Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen

In principle, textual context determines the ground-truth relation and the RE models should be able to correctly identify the relations reflected by the textual context.

Benchmarking Causal Inference +1

Take a Break in the Middle: Investigating Subgoals towards Hierarchical Script Generation

1 code implementation18 May 2023 Xinze Li, Yixin Cao, Muhao Chen, Aixin Sun

Goal-oriented Script Generation is a new task of generating a list of steps that can fulfill the given goal.

Context-faithful Prompting for Large Language Models

1 code implementation20 Mar 2023 Wenxuan Zhou, Sheng Zhang, Hoifung Poon, Muhao Chen

Large language models (LLMs) encode parametric knowledge about world facts and have shown remarkable performance in knowledge-driven NLP tasks.

Machine Reading Comprehension Relation Extraction

Continual Contrastive Finetuning Improves Low-Resource Relation Extraction

no code implementations21 Dec 2022 Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon

In this paper, we aim at bridging the gap and propose to pretrain and finetune the RE model using consistent objectives of contrastive learning.

Contrastive Learning Relation Extraction +2

Multi-hop Evidence Retrieval for Cross-document Relation Extraction

no code implementations21 Dec 2022 Keming Lu, I-Hung Hsu, Wenxuan Zhou, Mingyu Derek Ma, Muhao Chen

Additionally, we show that Mr. CoD facilitates evidence retrieval and boosts end-to-end RE performance with effective multi-hop reasoning in both closed and open settings of RE.

Relation Extraction Retrieval

Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?

1 code implementation21 Dec 2022 Jiashu Xu, Mingyu Derek Ma, Muhao Chen

Two key obstacles in biomedical relation extraction (RE) are the scarcity of annotations and the prevalence of instances without explicitly pre-defined labels due to low annotation coverage.

Multi-class Classification Natural Language Inference +1

PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales

1 code implementation3 Nov 2022 Peifeng Wang, Aaron Chan, Filip Ilievski, Muhao Chen, Xiang Ren

Neural language models (LMs) have achieved impressive results on various language-based reasoning tasks by utilizing latent knowledge encoded in their own pretrained parameters.

Decision Making

Salience Allocation as Guidance for Abstractive Summarization

1 code implementation22 Oct 2022 Fei Wang, Kaiqiang Song, Hongming Zhang, Lifeng Jin, Sangwoo Cho, Wenlin Yao, Xiaoyang Wang, Muhao Chen, Dong Yu

Recent literature adds extractive summaries as guidance for abstractive summarization models to provide hints of salient content and achieves better performance.

Abstractive Text Summarization

SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity Representation

no code implementations21 Oct 2022 Zekun Li, Jina Kim, Yao-Yi Chiang, Muhao Chen

Characterizing geo-entities is integral to various application domains, such as geo-intelligence and map comprehension, while a key challenge is to capture the spatial-varying context of an entity.

Entity Linking Entity Typing +2

Parameter-Efficient Tuning with Special Token Adaptation

1 code implementation10 Oct 2022 Xiaocong Yang, James Y. Huang, Wenxuan Zhou, Muhao Chen

Parameter-efficient tuning aims at updating only a small subset of parameters when adapting a pretrained model to downstream tasks.

Natural Language Understanding NER +2

Are All Steps Equally Important? Benchmarking Essentiality Detection of Events

no code implementations8 Oct 2022 Hongming Zhang, Yueguan Wang, Yuqian Deng, Haoyu Wang, Muhao Chen, Dan Roth

In this paper, we seek to fill this gap by studying how well current models can understand the essentiality of different step events towards a goal event.


VIPHY: Probing "Visible" Physical Commonsense Knowledge

1 code implementation15 Sep 2022 Shikhar Singh, Ehsan Qasemi, Muhao Chen

While such tasks measure the requisite knowledge to ground and reason over a given visual instance, they do not, however, measure the ability of VLMs to retain and generalize such knowledge.

Visual Reasoning

Bending the Future: Autoregressive Modeling of Temporal Knowledge Graphs in Curvature-Variable Hyperbolic Spaces

1 code implementation12 Sep 2022 Jihoon Sohn, Mingyu Derek Ma, Muhao Chen

The chronological hierarchies between knowledge graphs at different timestamps are represented by embedding the knowledge graphs as vectors in a common hyperbolic space.

Knowledge Graphs

Design and control analysis of a deployable clustered hyperbolic paraboloid cable net

no code implementations26 Jun 2022 Shuo Ma, Kai Lu, Muhao Chen, Robert E. Skelton

This paper presents an analytical and experimental design and deployment control analysis of a hyperbolic paraboloid cable net based on clustering actuation strategies.

Experimental Design

PInKS: Preconditioned Commonsense Inference with Minimal Supervision

no code implementations16 Jun 2022 Ehsan Qasemi, Piyush Khanna, Qiang Ning, Muhao Chen

Reasoning with preconditions such as "glass can be used for drinking water unless the glass is shattered" remains an open problem for language models.


Equilibrium and stiffness study of clustered tensegrity structures with the consideration of pulley sizes

no code implementations8 Jun 2022 Shuo Ma, Yiqian Chen, Muhao Chen, Robert E. Skelton

This paper presents the equilibrium and stiffness study of clustered tensegrity structures (CTS) considering pulley sizes.

Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing

1 code implementation25 May 2022 Nan Xu, Fei Wang, Bangzheng Li, Mingtao Dong, Muhao Chen

Due to shortcuts from surface patterns to annotated entity labels and biased training, existing entity typing models are subject to the problem of spurious correlations.

Data Augmentation Entity Typing

Summarization as Indirect Supervision for Relation Extraction

1 code implementation19 May 2022 Keming Lu, I-Hung Hsu, Wenxuan Zhou, Mingyu Derek Ma, Muhao Chen

Considering that summarization tasks aim at acquiring concise expressions of synoptical information from the longer context, these tasks naturally align with the objective of RE, i. e., extracting a kind of synoptical information that describes the relation of entity mentions.

Relation Extraction

GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction

no code implementations Findings (NAACL) 2022 Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Bryan Hooi

GRAPHCACHE aggregates the features from sentences in the whole dataset to learn global representations of properties, and use them to augment the local features within individual sentences.

Relation Extraction

Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis

1 code implementation NAACL 2022 Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, Bryan Hooi

In this paper, we propose the CORE (Counterfactual Analysis based Relation Extraction) debiasing method that guides the RE models to focus on the main effects of textual context without losing the entity information.

Relation Extraction

Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning

1 code implementation NAACL 2022 Fei Wang, Zhewei Xu, Pedro Szekely, Muhao Chen

This prunes the full self-attention structure into an order-invariant graph attention that captures the connected graph structure of cells belonging to the same row or column, and it differentiates between relevant cells and irrelevant cells from the structural perspective.

Data Augmentation Data-to-Text Generation +2

Unified Semantic Typing with Meaningful Label Inference

1 code implementation NAACL 2022 James Y. Huang, Bangzheng Li, Jiashu Xu, Muhao Chen

Semantic typing aims at classifying tokens or spans of interest in a textual context into semantic categories such as relations, entity types, and event types.

Entity Typing Relation Classification

Answer Consolidation: Formulation and Benchmarking

1 code implementation NAACL 2022 Wenxuan Zhou, Qiang Ning, Heba Elfardy, Kevin Small, Muhao Chen

Current question answering (QA) systems primarily consider the single-answer scenario, where each question is assumed to be paired with one correct answer.

Benchmarking Question Answering

Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference

1 code implementation12 Feb 2022 Bangzheng Li, Wenpeng Yin, Muhao Chen

The task of ultra-fine entity typing (UFET) seeks to predict diverse and free-form words or phrases that describe the appropriate types of entities mentioned in sentences.

Entity Typing Learning-To-Rank +2

Sharpness-Aware Minimization with Dynamic Reweighting

no code implementations16 Dec 2021 Wenxuan Zhou, Fangyu Liu, huan zhang, Muhao Chen

Deep neural networks are often overparameterized and may not easily achieve model generalization.

Natural Language Understanding

Contextualized Scene Imagination for Generative Commonsense Reasoning

1 code implementation ICLR 2022 Peifeng Wang, Jonathan Zamora, Junfeng Liu, Filip Ilievski, Muhao Chen, Xiang Ren

In this paper, we propose an Imagine-and-Verbalize (I&V) method, which learns to imagine a relational scene knowledge graph (SKG) with relations between the input concepts, and leverage the SKG as a constraint when generating a plausible scene description.

Common Sense Reasoning Story Generation

Structure-Aware Label Smoothing for Graph Neural Networks

no code implementations1 Dec 2021 Yiwei Wang, Yujun Cai, Yuxuan Liang, Wei Wang, Henghui Ding, Muhao Chen, Jing Tang, Bryan Hooi

Representing a label distribution as a one-hot vector is a common practice in training node classification models.

Classification Node Classification

Dynamics and control of clustered tensegrity systems

no code implementations17 Oct 2021 Shuo Ma, Muhao Chen, Robert E. Skelton

This paper presents the formulations of nonlinear and linearized statics, dynamics, and control for any clustered tensegrity system (CTS).

HyperExpan: Taxonomy Expansion with Hyperbolic Representation Learning

no code implementations Findings (EMNLP) 2021 Mingyu Derek Ma, Muhao Chen, Te-Lin Wu, Nanyun Peng

Taxonomies are valuable resources for many applications, but the limited coverage due to the expensive manual curation process hinders their general applicability.

Representation Learning Taxonomy Expansion

Salience-Aware Event Chain Modeling for Narrative Understanding

no code implementations EMNLP 2021 Xiyang Zhang, Muhao Chen, Jonathan May

Storytelling, whether via fables, news reports, documentaries, or memoirs, can be thought of as the communication of interesting and related events that, taken together, form a concrete process.

Question Answering

Learning Constraints and Descriptive Segmentation for Subevent Detection

no code implementations EMNLP 2021 Haoyu Wang, Hongming Zhang, Muhao Chen, Dan Roth

The task of subevent detection aims to resolve this granularity issue, recognizing the membership of multi-granular events in event complexes.

Text Segmentation

Table-based Fact Verification with Salience-aware Learning

1 code implementation Findings (EMNLP) 2021 Fei Wang, Kexuan Sun, Jay Pujara, Pedro Szekely, Muhao Chen

From one perspective, our system conducts masked salient token prediction to enhance the model for alignment and reasoning between the table and the statement.

Data Augmentation Fact Verification +1

Event-Centric Natural Language Processing

no code implementations ACL 2021 Muhao Chen, Hongming Zhang, Qiang Ning, Manling Li, Heng Ji, Kathleen McKeown, Dan Roth

This tutorial targets researchers and practitioners who are interested in AI technologies that help machines understand natural language text, particularly real-world events described in the text.

Do Language Models Perform Generalizable Commonsense Inference?

1 code implementation Findings (ACL) 2021 Peifeng Wang, Filip Ilievski, Muhao Chen, Xiang Ren

Inspired by evidence that pretrained language models (LMs) encode commonsense knowledge, recent work has applied LMs to automatically populate commonsense knowledge graphs (CKGs).

Knowledge Graphs

Design and analysis of deployable clustered tensegrity cable domes

no code implementations15 Jun 2021 Shuo Ma, Muhao Chen, Xingfei Yuan, Robert E. Skelton

Results show that the proposed CTS cable dome always has one prestress mode and is globally stable in its deployment trajectory.

Knowing the No-match: Entity Alignment with Dangling Cases

1 code implementation ACL 2021 Zequn Sun, Muhao Chen, Wei Hu

Since KGs possess different sets of entities, there could be entities that cannot find alignment across them, leading to the problem of dangling entities.

Abstention Prediction Entity Alignment +1

Retrieving Complex Tables with Multi-Granular Graph Representation Learning

1 code implementation4 May 2021 Fei Wang, Kexuan Sun, Muhao Chen, Jay Pujara, Pedro Szekely

The task of natural language table retrieval (NLTR) seeks to retrieve semantically relevant tables based on natural language queries.

Graph Representation Learning Natural Language Queries +2

PaCo: Preconditions Attributed to Commonsense Knowledge

no code implementations18 Apr 2021 Ehsan Qasemi, Filip Ilievski, Muhao Chen, Pedro Szekely

To address this gap, we propose a novel challenge of reasoning with circumstantial preconditions.

Common Sense Reasoning

Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning

1 code implementation NAACL 2021 Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum

Knowledge bases often consist of facts which are harvested from a variety of sources, many of which are noisy and some of which conflict, resulting in a level of uncertainty for each triple.

Knowledge Graph Embedding

Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts

1 code implementation15 Mar 2021 Junheng Hao, Muhao Chen, Wenchao Yu, Yizhou Sun, Wei Wang

The cross-view association model is learned to bridge the embeddings of ontological concepts and their corresponding instance-view entities.

Entity Typing Knowledge Graphs +1

Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases

1 code implementation7 Mar 2021 Junheng Hao, Chelsea Ju, Muhao Chen, Yizhou Sun, Carlo Zaniolo, Wei Wang

Leveraging a wide-range of biological knowledge, such as gene ontology and protein-protein interaction (PPI) networks from other closely related species presents a vital approach to infer the molecular impact of a new species.

Representation Learning Type prediction

An Improved Baseline for Sentence-level Relation Extraction

1 code implementation2 Feb 2021 Wenxuan Zhou, Muhao Chen

Sentence-level relation extraction (RE) aims at identifying the relationship between two entities in a sentence.

Relation Extraction

Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks

1 code implementation15 Dec 2020 Cunchao Zhu, Muhao Chen, Changjun Fan, Guangquan Cheng, Yan Zhan

Since such temporal knowledge graphs often suffer from incompleteness, it is important to develop time-aware representation learning models that help to infer the missing temporal facts.

Representation Learning

What Are You Trying to Do? Semantic Typing of Event Processes

no code implementations CONLL 2020 Muhao Chen, Hongming Zhang, Haoyu Wang, Dan Roth

This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given anevent process, attempts to infer free-form typelabels describing (i) the type of action made bythe process and (ii) the type of object the pro-cess seeks to affect.

Learning-To-Rank Vocal Bursts Type Prediction

Analogous Process Structure Induction for Sub-event Sequence Prediction

no code implementations EMNLP 2020 Hongming Zhang, Muhao Chen, Haoyu Wang, Yangqiu Song, Dan Roth

Computational and cognitive studies of event understanding suggest that identifying, comprehending, and predicting events depend on having structured representations of a sequence of events and on conceptualizing (abstracting) its components into (soft) event categories.

Joint Constrained Learning for Event-Event Relation Extraction

no code implementations EMNLP 2020 Haoyu Wang, Muhao Chen, Hongming Zhang, Dan Roth

Understanding natural language involves recognizing how multiple event mentions structurally and temporally interact with each other.

Event Relation Extraction Temporal Relation Extraction

"What Are You Trying to Do?" Semantic Typing of Event Processes

no code implementations13 Oct 2020 Muhao Chen, Hongming Zhang, Haoyu Wang, Dan Roth

This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given an event process, attempts to infer free-form type labels describing (i) the type of action made by the process and (ii) the type of object the process seeks to affect.

Learning-To-Rank Vocal Bursts Type Prediction

Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer

1 code implementation Findings of the Association for Computational Linguistics 2020 Xuelu Chen, Muhao Chen, Changjun Fan, Ankith Uppunda, Yizhou Sun, Carlo Zaniolo

Predicting missing facts in a knowledge graph (KG) is a crucial task in knowledge base construction and reasoning, and it has been the subject of much research in recent works using KG embeddings.

Knowledge Graph Completion Self-Learning +1

Knowledge Association with Hyperbolic Knowledge Graph Embeddings

1 code implementation EMNLP 2020 Zequn Sun, Muhao Chen, Wei Hu, Chengming Wang, Jian Dai, Wei zhang

Capturing associations for knowledge graphs (KGs) through entity alignment, entity type inference and other related tasks benefits NLP applications with comprehensive knowledge representations.

Entity Alignment Knowledge Graph Embeddings +1

Visual Pivoting for (Unsupervised) Entity Alignment

2 code implementations28 Sep 2020 Fangyu Liu, Muhao Chen, Dan Roth, Nigel Collier

This work studies the use of visual semantic representations to align entities in heterogeneous knowledge graphs (KGs).

Ranked #11 on Entity Alignment on dbp15k ja-en (using extra training data)

Entity Alignment Knowledge Graphs

Cross-lingual Entity Alignment with Incidental Supervision

1 code implementation EACL 2021 Muhao Chen, Weijia Shi, Ben Zhou, Dan Roth

Much research effort has been put to multilingual knowledge graph (KG) embedding methods to address the entity alignment task, which seeks to match entities in different languagespecific KGs that refer to the same real-world object.

Entity Alignment Knowledge Graphs

A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs

1 code implementation10 Mar 2020 Zequn Sun, Qingheng Zhang, Wei Hu, Chengming Wang, Muhao Chen, Farahnaz Akrami, Chengkai Li

Recent advancement in KG embedding impels the advent of embedding-based entity alignment, which encodes entities in a continuous embedding space and measures entity similarities based on the learned embeddings.

Benchmarking Entity Alignment +1

Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation

1 code implementation20 Nov 2019 Zequn Sun, Chengming Wang, Wei Hu, Muhao Chen, Jian Dai, Wei zhang, Yuzhong Qu

As the direct neighbors of counterpart entities are usually dissimilar due to the schema heterogeneity, AliNet introduces distant neighbors to expand the overlap between their neighborhood structures.

Entity Alignment Knowledge Graphs

Fast and Accurate Network Embeddings via Very Sparse Random Projection

1 code implementation30 Aug 2019 Haochen Chen, Syed Fahad Sultan, Yingtao Tian, Muhao Chen, Steven Skiena

Two key features of FastRP are: 1) it explicitly constructs a node similarity matrix that captures transitive relationships in a graph and normalizes matrix entries based on node degrees; 2) it utilizes very sparse random projection, which is a scalable optimization-free method for dimension reduction.

Dimensionality Reduction Network Embedding

Learning Bilingual Word Embeddings Using Lexical Definitions

no code implementations WS 2019 Weijia Shi, Muhao Chen, Yingtao Tian, Kai-Wei Chang

Bilingual word embeddings, which representlexicons of different languages in a shared em-bedding space, are essential for supporting se-mantic and knowledge transfers in a variety ofcross-lingual NLP tasks.

Translation Word Alignment +1

Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach

1 code implementation24 May 2019 Changjun Fan, Li Zeng, Yuhui Ding, Muhao Chen, Yizhou Sun, Zhong Liu

By training on small-scale networks, the learned model is capable of assigning relative BC scores to nodes for any unseen networks, and thus identifying the highly-ranked nodes.

Community Detection

Quantification and Analysis of Scientific Language Variation Across Research Fields

no code implementations4 Dec 2018 Pei Zhou, Muhao Chen, Kai-Wei Chang, Carlo Zaniolo

Quantifying differences in terminologies from various academic domains has been a longstanding problem yet to be solved.

Language Modelling

Embedding Uncertain Knowledge Graphs

1 code implementation26 Nov 2018 Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun, Carlo Zaniolo

However, there are many KGs that model uncertain knowledge, which typically model the inherent uncertainty of relations facts with a confidence score, and embedding such uncertain knowledge represents an unresolved challenge.

Binary Classification General Classification +2

Enhanced Network Embeddings via Exploiting Edge Labels

1 code implementation13 Sep 2018 Haochen Chen, Xiaofei Sun, Yingtao Tian, Bryan Perozzi, Muhao Chen, Steven Skiena

Network embedding methods aim at learning low-dimensional latent representation of nodes in a network.

Social and Information Networks Physics and Society

On2Vec: Embedding-based Relation Prediction for Ontology Population

no code implementations7 Sep 2018 Muhao Chen, Yingtao Tian, Xuelu Chen, Zijun Xue, Carlo Zaniolo

Recent advances in translation-based graph embedding methods for populating instance-level knowledge graphs lead to promising new approaching for the ontology population problem.

Graph Embedding Knowledge Graphs +1

Neural Article Pair Modeling for Wikipedia Sub-article Matching

1 code implementation31 Jul 2018 Muhao Chen, Changping Meng, Gang Huang, Carlo Zaniolo

Nowadays, editors tend to separate different subtopics of a long Wiki-pedia article into multiple sub-articles.

Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment

no code implementations18 Jun 2018 Muhao Chen, Yingtao Tian, Kai-Wei Chang, Steven Skiena, Carlo Zaniolo

Since many multilingual KGs also provide literal descriptions of entities, in this paper, we introduce an embedding-based approach which leverages a weakly aligned multilingual KG for semi-supervised cross-lingual learning using entity descriptions.

Entity Alignment Knowledge Graphs

Attention-based Natural Language Person Retrieval

no code implementations24 May 2017 Tao Zhou, Muhao Chen, Jie Yu, Demetri Terzopoulos

Following the recent progress in image classification and captioning using deep learning, we develop a novel natural language person retrieval system based on an attention mechanism.

Image Classification Person Retrieval +2

Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

2 code implementations12 Nov 2016 Muhao Chen, Yingtao Tian, Mohan Yang, Carlo Zaniolo

Many recent works have demonstrated the benefits of knowledge graph embeddings in completing monolingual knowledge graphs.

Entity Alignment Knowledge Graph Embeddings +2

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