Search Results for author: Yixin Cao

Found 66 papers, 38 papers with code

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

1 code implementation 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

Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better

1 code implementation24 Apr 2024 Vicente Balmaseda, Ying Xu, Yixin Cao, Nate Veldt

Cluster deletion is an NP-hard graph clustering objective with applications in computational biology and social network analysis, where the goal is to delete a minimum number of edges to partition a graph into cliques.

Graph Clustering

Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective

no code implementations27 Mar 2024 Meiqi Chen, Yixin Cao, Yan Zhang, Chaochao Lu

Within our framework, we devise a causal graph to elucidate the predictions of MLLMs on VQA problems, and assess the causal effect of biases through an in-depth causal analysis.

Question Answering Visual Question Answering

Meaningful Learning: Advancing Abstract Reasoning in Large Language Models via Generic Fact Guidance

no code implementations14 Mar 2024 Kai Xiong, Xiao Ding, Ting Liu, Bing Qin, Dongliang Xu, Qing Yang, Hongtao Liu, Yixin Cao

Large language models (LLMs) have developed impressive performance and strong explainability across various reasoning scenarios, marking a significant stride towards mimicking human-like intelligence.


Event-level Knowledge Editing

1 code implementation20 Feb 2024 Hao Peng, Xiaozhi Wang, Chunyang Li, Kaisheng Zeng, Jiangshan Duo, Yixin Cao, Lei Hou, Juanzi Li

However, natural knowledge updates in the real world come from the occurrences of new events rather than direct changes in factual triplets.

knowledge editing

Have Seen Me Before? Automating Dataset Updates Towards Reliable and Timely Evaluation

no code implementations19 Feb 2024 Jiahao Ying, Yixin Cao, Bo wang, Wei Tang, Yizhe Yang, Shuicheng Yan

The basic idea is to generate unseen and high-quality testing samples based on existing ones to mitigate leakage issues.

SciAgent: Tool-augmented Language Models for Scientific Reasoning

no code implementations18 Feb 2024 Yubo Ma, Zhibin Gou, Junheng Hao, Ruochen Xu, Shuohang Wang, Liangming Pan, Yujiu Yang, Yixin Cao, Aixin Sun, Hany Awadalla, Weizhu Chen

To make this task more practical and solvable for LLMs, we introduce a new task setting named tool-augmented scientific reasoning.

FedMKGC: Privacy-Preserving Federated Multilingual Knowledge Graph Completion

no code implementations17 Dec 2023 Wei Tang, Zhiqian Wu, Yixin Cao, Yong Liao, Pengyuan Zhou

As such, the aggregated language model can leverage complementary knowledge from multilingual KGs without demanding raw user data sharing.

Entity Alignment Federated Learning +3

SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting

1 code implementation2 Dec 2023 Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Liang Pang, Tat-Seng Chua

Temporal complex event forecasting aims to predict the future events given the observed events from history.

X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects

no code implementations15 Nov 2023 Minqian Liu, Ying Shen, Zhiyang Xu, Yixin Cao, Eunah Cho, Vaibhav Kumar, Reza Ghanadan, Lifu Huang

Natural Language Generation (NLG) typically involves evaluating the generated text in various aspects (e. g., consistency and naturalness) to obtain a comprehensive assessment.

Dialogue Generation Language Modelling +2

Finding and Editing Multi-Modal Neurons in Pre-Trained Transformer

1 code implementation13 Nov 2023 Haowen Pan, Yixin Cao, Xiaozhi Wang, Xun Yang

Multi-modal large language models (LLM) have achieved powerful capabilities for visual semantic understanding in recent years.

knowledge editing

A Comprehensive Evaluation of Large Language Models on Legal Judgment Prediction

1 code implementation18 Oct 2023 Ruihao Shui, Yixin Cao, Xiang Wang, Tat-Seng Chua

Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain.

Information Retrieval Legal Reasoning +1

Learning To Teach Large Language Models Logical Reasoning

1 code implementation13 Oct 2023 Meiqi Chen, Yubo Ma, Kaitao Song, Yixin Cao, Yan Zhang, Dongsheng Li

Large language models (LLMs) have gained enormous attention from both academia and industry, due to their exceptional ability in language generation and extremely powerful generalization.

counterfactual Event Relation Extraction +4

Intuitive or Dependent? Investigating LLMs' Behavior Style to Conflicting Prompts

no code implementations29 Sep 2023 Jiahao Ying, Yixin Cao, Kai Xiong, Yidong He, Long Cui, Yongbin Liu

Drawing on cognitive theory, we target the first scenario of decision-making styles where there is no superiority in the conflict and categorize LLMs' preference into dependent, intuitive, and rational/irrational styles.

Benchmarking Decision Making +1

FOLLOWUPQG: Towards Information-Seeking Follow-up Question Generation

1 code implementation10 Sep 2023 Yan Meng, Liangming Pan, Yixin Cao, Min-Yen Kan

We introduce the task of real-world information-seeking follow-up question generation (FQG), which aims to generate follow-up questions seeking a more in-depth understanding of an initial question and answer.

Informativeness Question Generation +1

Context-aware Event Forecasting via Graph Disentanglement

1 code implementation12 Aug 2023 Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua

The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future.

Disentanglement Link Prediction

Constructing Holistic Spatio-Temporal Scene Graph for Video Semantic Role Labeling

no code implementations9 Aug 2023 Yu Zhao, Hao Fei, Yixin Cao, Bobo Li, Meishan Zhang, Jianguo Wei, Min Zhang, Tat-Seng Chua

A scene-event mapping mechanism is first designed to bridge the gap between the underlying scene structure and the high-level event semantic structure, resulting in an overall hierarchical scene-event (termed ICE) graph structure.

Semantic Role Labeling

Robust Prompt Optimization for Large Language Models Against Distribution Shifts

no code implementations23 May 2023 Moxin Li, Wenjie Wang, Fuli Feng, Yixin Cao, Jizhi Zhang, Tat-Seng Chua

In this light, we propose a new problem of robust prompt optimization for LLMs against distribution shifts, which requires the prompt optimized over the labeled source group can simultaneously generalize to an unlabeled target group.

Language Modelling Large Language Model

Information Screening whilst Exploiting! Multimodal Relation Extraction with Feature Denoising and Multimodal Topic Modeling

1 code implementation19 May 2023 Shengqiong Wu, Hao Fei, Yixin Cao, Lidong Bing, Tat-Seng Chua

First, we represent the fine-grained semantic structures of the input image and text with the visual and textual scene graphs, which are further fused into a unified cross-modal graph (CMG).

Denoising Relation +1

Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate

1 code implementation19 May 2023 Kai Xiong, Xiao Ding, Yixin Cao, Ting Liu, Bing Qin

Through extensive experiments on various datasets, LLMs can effectively collaborate to reach a consensus despite noticeable inter-inconsistencies, but imbalances in their abilities can lead to domination by superior LLMs.

Decision Making

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.

Few-shot Event Detection: An Empirical Study and a Unified View

1 code implementation3 May 2023 Yubo Ma, Zehao Wang, Yixin Cao, Aixin Sun

Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e. g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress. This paper presents a thorough empirical study, a unified view of ED models, and a better unified baseline.

Event Detection

R$^2$F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

1 code implementation22 Oct 2022 Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.

Natural Language Inference Retrieval +1

TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning

1 code implementation11 Oct 2022 Linhai Zhuo, Yuqian Fu, Jingjing Chen, Yixin Cao, Yu-Gang Jiang

The proposed TGDM framework contains a Mixup-3T network for learning classifiers and a dynamic ratio generation network (DRGN) for learning the optimal mix ratio.

cross-domain few-shot learning Transfer Learning

VEM$^2$L: A Plug-and-play Framework for Fusing Text and Structure Knowledge on Sparse Knowledge Graph Completion

no code implementations4 Jul 2022 Tao He, Ming Liu, Yixin Cao, Tianwen Jiang, Zihao Zheng, Jingrun Zhang, Sendong Zhao, Bing Qin

In this paper, we solve the sparse KGC from these two motivations simultaneously and handle their respective drawbacks further, and propose a plug-and-play unified framework VEM$^2$L over sparse KGs.

Knowledge Distillation Missing Elements +1

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

no code implementations COLING 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.

Event Causality Identification Node Classification +2

Information Extraction in Low-Resource Scenarios: Survey and Perspective

2 code implementations16 Feb 2022 Shumin Deng, Yubo Ma, Ningyu Zhang, Yixin Cao, Bryan Hooi

Information Extraction (IE) seeks to derive structured information from unstructured texts, often facing challenges in low-resource scenarios due to data scarcity and unseen classes.

What Makes the Story Forward? Inferring Commonsense Explanations as Prompts for Future Event Generation

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

To alleviate the knowledge forgetting issue, we design two modules, Im and Gm, for each type of knowledge, which are combined via prompt tuning.

Information Retrieval Retrieval +1

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 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 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.

Benchmarking 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 Relation Extraction +1

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.

Retrieval 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 Relation Extraction

KGAT: Knowledge Graph Attention Network for Recommendation

7 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.

Explainable Recommendation Knowledge Graphs +1

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.

Explainable Recommendation 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.

Clustering Language Modelling +3

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