Search Results for author: Yixin Cao

Found 34 papers, 19 papers with code

Do Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach

no code implementations Findings (ACL) 2022 Xin Lv, Yankai Lin, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Peng Li, Jie zhou

In recent years, pre-trained language models (PLMs) have been shown to capture factual knowledge from massive texts, which encourages the proposal of PLM-based knowledge graph completion (KGC) models.

Knowledge Graph Completion Link Prediction

ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification

no code implementations15 Apr 2022 Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang

In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework for DECI, which improves existing state-of-the-art (SOTA) methods upon two aspects.

Node Classification Relation Classification

Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction

1 code implementation ACL 2022 Yubo Ma, Zehao Wang, Yixin Cao, Mukai Li, Meiqi Chen, Kun Wang, Jing Shao

We have conducted extensive experiments on three benchmarks, including both sentence- and document-level EAE.

Inferring Commonsense Explanations as Prompts for Future Event Generation

no code implementations18 Jan 2022 Li Lin, Yixin Cao, Lifu Huang, Shuang Li, Xuming Hu, Lijie Wen, Jianmin Wang

GM further takes the commonsense knowledge as prompts to guide and enforce the generation of logistically coherent future events.

Text Generation

ICLEA: Interactive Contrastive Learning for Self-supervised Entity Alignment

no code implementations17 Jan 2022 Kaisheng Zeng, Zhenhao Dong, Lei Hou, Yixin Cao, Minghao Hu, Jifan Yu, Xin Lv, Juanzi Li, Ling Feng

Self-supervised entity alignment (EA) aims to link equivalent entities across different knowledge graphs (KGs) without seed alignments.

Contrastive Learning Entity Alignment +1

Training Free Graph Neural Networks for Graph Matching

1 code implementation14 Jan 2022 Zhiyuan Liu, Yixin Cao, Fuli Feng, Xiang Wang, Jie Tang, Kenji Kawaguchi, Tat-Seng Chua

We present a framework of Training Free Graph Matching (TFGM) to boost the performance of Graph Neural Networks (GNNs) based graph matching, providing a fast promising solution without training (training-free).

Entity Alignment Graph Matching +1

Are Missing Links Predictable? An Inferential Benchmark for Knowledge Graph Completion

1 code implementation ACL 2021 Yixin Cao, Xiang Ji, Xin Lv, Juanzi Li, Yonggang Wen, Hanwang Zhang

We present InferWiki, a Knowledge Graph Completion (KGC) dataset that improves upon existing benchmarks in inferential ability, assumptions, and patterns.

Knowledge Graph Completion

How Knowledge Graph and Attention Help? A Qualitative Analysis into Bag-level Relation Extraction

1 code implementation ACL 2021 Zikun Hu, Yixin Cao, Lifu Huang, Tat-Seng Chua

In this paper, we contribute a dataset and propose a paradigm to quantitatively evaluate the effect of attention and KG on bag-level relation extraction (RE).

Relation Extraction

How Knowledge Graph and Attention Help? A Quantitative Analysis into Bag-level Relation Extraction

1 code implementation26 Jul 2021 Zikun Hu, Yixin Cao, Lifu Huang, Tat-Seng Chua

In this paper, we contribute a dataset and propose a paradigm to quantitatively evaluate the effect of attention and KG on bag-level relation extraction (RE).

Relation Extraction

Is Multi-Hop Reasoning Really Explainable? Towards Benchmarking Reasoning Interpretability

1 code implementation EMNLP 2021 Xin Lv, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Yichi Zhang, Zelin Dai

However, we find in experiments that many paths given by these models are actually unreasonable, while little works have been done on interpretability evaluation for them.

Link Prediction

Flashot: A Snapshot of Flash Loan Attack on DeFi Ecosystem

no code implementations1 Feb 2021 Yixin Cao, Chuanwei Zou, Xianfeng Cheng

Flash Loan attack can grab millions of dollars from decentralized vaults in one single transaction, drawing increasing attention from the Decentralized Finance (DeFi) players.

Learning Relation Prototype from Unlabeled Texts for Long-tail Relation Extraction

1 code implementation27 Nov 2020 Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua

In this paper, we propose a general approach to learn relation prototypesfrom unlabeled texts, to facilitate the long-tail relation extraction by transferring knowledge from the relation types with sufficient trainingdata.

Relation Extraction Transfer Learning

Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval

no code implementations6 Jul 2020 Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, Tat-Seng Chua

To facilitate video retrieval with complex queries, we propose a Tree-augmented Cross-modal Encoding method by jointly learning the linguistic structure of queries and the temporal representation of videos.

Video Retrieval

Reinforced Negative Sampling over Knowledge Graph for Recommendation

1 code implementation12 Mar 2020 Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Meng Wang, Tat-Seng Chua

Properly handling missing data is a fundamental challenge in recommendation.

Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model

1 code implementation IJCNLP 2019 Chengjiang Li, Yixin Cao, Lei Hou, Jiaxin Shi, Juanzi Li, Tat-Seng Chua

Specifically, as for the knowledge embedding model, we utilize TransE to implicitly complete two KGs towards consistency and learn relational constraints between entities.

Entity Alignment Graph Attention +1

Low-Resource Name Tagging Learned with Weakly Labeled Data

1 code implementation IJCNLP 2019 Yixin Cao, Zikun Hu, Tat-Seng Chua, Zhiyuan Liu, Heng Ji

Name tagging in low-resource languages or domains suffers from inadequate training data.


Who, Where, and What to Wear? Extracting Fashion Knowledge from Social Media

no code implementations12 Aug 2019 Yunshan Ma, Xun Yang, Lizi Liao, Yixin Cao, Tat-Seng Chua

We unify three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata.

Human Detection

Improving Neural Relation Extraction with Implicit Mutual Relations

1 code implementation8 Jul 2019 Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou

In contrast to existing distant supervision approaches that suffer from insufficient training corpora to extract relations, our proposal of mining implicit mutual relation from the massive unlabeled corpora transfers the semantic information of entity pairs into the RE model, which is more expressive and semantically plausible.

Relation Extraction

KGAT: Knowledge Graph Attention Network for Recommendation

6 code implementations20 May 2019 Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua

To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account.

Graph Attention Knowledge Graphs +2

Neural Collective Entity Linking

1 code implementation COLING 2018 Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu

To address this issue, we propose a novel neural model for collective entity linking, named as NCEL.

Entity Linking

Explainable Reasoning over Knowledge Graphs for Recommendation

2 code implementations12 Nov 2018 Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, Tat-Seng Chua

Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user's interest.

Knowledge Graphs Recommendation Systems

Visually Explainable Recommendation

no code implementations31 Jan 2018 Xu Chen, Yongfeng Zhang, Hongteng Xu, Yixin Cao, Zheng Qin, Hongyuan Zha

By this, we can not only provide recommendation results to the users, but also tell the users why an item is recommended by providing intuitive visual highlights in a personalized manner.

Recommendation Systems

On Modeling Sense Relatedness in Multi-prototype Word Embedding

no code implementations IJCNLP 2017 Yixin Cao, Jiaxin Shi, Juanzi Li, Zhiyuan Liu, Chengjiang Li

To enhance the expression ability of distributional word representation learning model, many researchers tend to induce word senses through clustering, and learn multiple embedding vectors for each word, namely multi-prototype word embedding model.

Language Modelling Named Entity Recognition +2

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