Search Results for author: Jing Ma

Found 60 papers, 26 papers with code

HiTRANS: A Hierarchical Transformer Network for Nested Named Entity Recognition

no code implementations Findings (EMNLP) 2021 Zhiwei Yang, Jing Ma, Hechang Chen, Yunke Zhang, Yi Chang

Specifically, we first utilize a two-phase module to generate span representations by aggregating context information based on a bottom-up and top-down transformer network.

named-entity-recognition Named Entity Recognition +3

AnswerFact: Fact Checking in Product Question Answering

no code implementations EMNLP 2020 Wenxuan Zhang, Yang Deng, Jing Ma, Wai Lam

Product-related question answering platforms nowadays are widely employed in many E-commerce sites, providing a convenient way for potential customers to address their concerns during online shopping.

Fact Checking Misinformation +1

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models

1 code implementation24 Jan 2024 Hongzhan Lin, Ziyang Luo, Wei Gao, Jing Ma, Bo wang, Ruichao Yang

Then we propose to fine-tune a small language model as the debate judge for harmfulness inference, to facilitate multimodal fusion between the harmfulness rationales and the intrinsic multimodal information within memes.

Language Modelling Text Generation

Cyclic Neural Network

no code implementations11 Jan 2024 Liangwei Yang, Hengrui Zhang, Zihe Song, Jiawei Zhang, Weizhi Zhang, Jing Ma, Philip S. Yu

This paper answers a fundamental question in artificial neural network (ANN) design: We do not need to build ANNs layer-by-layer sequentially to guarantee the Directed Acyclic Graph (DAG) property.

GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse

no code implementations3 Jan 2024 Hongzhan Lin, Ziyang Luo, Bo wang, Ruichao Yang, Jing Ma

The exponential growth of social media has profoundly transformed how information is created, disseminated, and absorbed, exceeding any precedent in the digital age.

Efficient LLM inference solution on Intel GPU

1 code implementation19 Dec 2023 Hui Wu, Yi Gan, Feng Yuan, Jing Ma, Wei Zhu, Yutao Xu, Hong Zhu, Yuhua Zhu, Xiaoli Liu, Jinghui Gu

A customized Scaled-Dot-Product-Attention kernel is designed to match our fusion policy based on the segment KV cache solution.


WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdom

1 code implementation25 Oct 2023 Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Zhiwei Yang

This model only requires bag-level labels for training but is capable of inferring both sentence-level misinformation and article-level veracity, aided by relevant social media conversations that are attentively contextualized with news sentences.

Misinformation Multiple Instance Learning +2

Fair Few-shot Learning with Auxiliary Sets

no code implementations28 Aug 2023 Song Wang, Jing Ma, Lu Cheng, Jundong Li

These auxiliary sets contain several labeled training samples that can enhance the model performance regarding fairness in meta-test tasks, thereby allowing for the transfer of learned useful fairness-oriented knowledge to meta-test tasks.

Fairness Few-Shot Learning +1

Graph-based Alignment and Uniformity for Recommendation

1 code implementation18 Aug 2023 Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu

To address this issue, we propose a novel approach, graph-based alignment and uniformity (GraphAU), that explicitly considers high-order connectivities in the user-item bipartite graph.

Collaborative Filtering Recommendation Systems +1

Learning for Counterfactual Fairness from Observational Data

no code implementations17 Jul 2023 Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li

A prerequisite for existing methods to achieve counterfactual fairness is the prior human knowledge of the causal model for the data.

Attribute Causal Discovery +4

WizardCoder: Empowering Code Large Language Models with Evol-Instruct

2 code implementations14 Jun 2023 Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, QIngwei Lin, Daxin Jiang

Moreover, our model even outperforms the largest closed LLMs, Anthropic's Claude and Google's Bard, on HumanEval and HumanEval+.

Ranked #3 on Code Generation on CodeContests (Test Set pass@1 metric)

Code Generation

Path-Specific Counterfactual Fairness for Recommender Systems

1 code implementation5 Jun 2023 Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li

But since sensitive features may also affect user interests in a fair manner (e. g., race on culture-based preferences), indiscriminately eliminating all the influences of sensitive features inevitably degenerate the recommendations quality and necessary diversities.

Blocking counterfactual +4

Augmented Large Language Models with Parametric Knowledge Guiding

1 code implementation8 May 2023 Ziyang Luo, Can Xu, Pu Zhao, Xiubo Geng, Chongyang Tao, Jing Ma, QIngwei Lin, Daxin Jiang

We demonstrate that our PKG framework can enhance the performance of "black-box" LLMs on a range of domain knowledge-intensive tasks that require factual (+7. 9%), tabular (+11. 9%), medical (+3. 0%), and multimodal (+8. 1%) knowledge.

Cluster-based Deep Ensemble Learning for Emotion Classification in Internet Memes

no code implementations16 Feb 2023 XIAOYU GUO, Jing Ma, Arkaitz Zubiaga

Memes have gained popularity as a means to share visual ideas through the Internet and social media by mixing text, images and videos, often for humorous purposes.

Clustering Emotion Classification +1

LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Retrieval

1 code implementation6 Feb 2023 Ziyang Luo, Pu Zhao, Can Xu, Xiubo Geng, Tao Shen, Chongyang Tao, Jing Ma, Qingwen Lin, Daxin Jiang

The conventional dense retrieval paradigm relies on encoding images and texts into dense representations using dual-stream encoders, however, it faces challenges with low retrieval speed in large-scale retrieval scenarios.

Retrieval Text Retrieval

Causal Inference in Recommender Systems: A Survey of Strategies for Bias Mitigation, Explanation, and Generalization

1 code implementation3 Jan 2023 Yaochen Zhu, Jing Ma, Jundong Li

Traditional RSs estimate user interests and predict their future behaviors by utilizing correlations in the observational historical activities, their profiles, and the content of interacted items.

Causal Inference Recommendation Systems

LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Sparse Retrieval

1 code implementation ICCV 2023 Ziyang Luo, Pu Zhao, Can Xu, Xiubo Geng, Tao Shen, Chongyang Tao, Jing Ma, QIngwei Lin, Daxin Jiang

To address this issue, we propose a novel sparse retrieval paradigm for ITR that exploits sparse representations in the vocabulary space for images and texts.

Image Classification Retrieval +2

Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning

1 code implementation2 Dec 2022 Hongzhan Lin, Pengyao Yi, Jing Ma, Haiyun Jiang, Ziyang Luo, Shuming Shi, Ruifang Liu

The spread of rumors along with breaking events seriously hinders the truth in the era of social media.

Domain Adaptation

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution

1 code implementation25 Nov 2022 Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

In this paper, we study a novel problem of interpreting GNN unfairness through attributing it to the influence of training nodes.

Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels

no code implementations3 Nov 2022 Qiuchen Zhang, Jing Ma, Jian Lou, Li Xiong, Xiaoqian Jiang

PATE combines an ensemble of "teacher models" trained on sensitive data and transfers the knowledge to a "student" model through the noisy aggregation of teachers' votes for labeling unlabeled public data which the student model will be trained on.

Transfer Learning

CLEAR: Generative Counterfactual Explanations on Graphs

no code implementations16 Oct 2022 Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

Counterfactual explanations promote explainability in machine learning models by answering the question "how should an input instance be perturbed to obtain a desired predicted label?".

counterfactual Counterfactual Explanation +1

Towards Training Graph Neural Networks with Node-Level Differential Privacy

no code implementations10 Oct 2022 Qiuchen Zhang, Jing Ma, Jian Lou, Carl Yang, Li Xiong

Furthermore, we analyze the privacy degradation caused by the sampling process dependent on the differentially private PageRank results during model training and propose a differentially private GNN (DPGNN) algorithm to further protect node features and achieve rigorous node-level differential privacy.

A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection

1 code implementation COLING 2022 Zhiwei Yang, Jing Ma, Hechang Chen, Hongzhan Lin, Ziyang Luo, Yi Chang

Existing fake news detection methods aim to classify a piece of news as true or false and provide veracity explanations, achieving remarkable performances.

Fake News Detection

Learning Causal Effects on Hypergraphs

no code implementations7 Jul 2022 Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan

Hypergraphs provide an effective abstraction for modeling multi-way group interactions among nodes, where each hyperedge can connect any number of nodes.

Mapping Emulation for Knowledge Distillation

no code implementations21 May 2022 Jing Ma, Xiang Xiang, Zihan Zhang, Yuwen Tan, Yiming Wan, Zhigang Zeng, DaCheng Tao

A new geometric perspective is presented to view such a problem as aligning generated distributions between the teacher and student.

Federated Learning Knowledge Distillation

Empowering Next POI Recommendation with Multi-Relational Modeling

no code implementations24 Apr 2022 Zheng Huang, Jing Ma, Yushun Dong, Natasha Zhang Foutz, Jundong Li

Noticeably, LBSNs have offered unparalleled access to abundant heterogeneous relational information about users and POIs (including user-user social relations, such as families or colleagues; and user-POI visiting relations).

Representation Learning

Fairness in Graph Mining: A Survey

2 code implementations21 Apr 2022 Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li

Recently, algorithmic fairness has been extensively studied in graph-based applications.

Fairness Graph Mining

A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning

no code implementations6 Apr 2022 Ruichao Yang, Jing Ma, Hongzhan Lin, Wei Gao

The diffusion of rumors on microblogs generally follows a propagation tree structure, that provides valuable clues on how an original message is transmitted and responded by users over time.

Binary Classification Multiple Instance Learning +2

I-Tuning: Tuning Frozen Language Models with Image for Lightweight Image Captioning

no code implementations14 Feb 2022 Ziyang Luo, Zhipeng Hu, Yadong Xi, Rongsheng Zhang, Jing Ma

Different to these heavy-cost models, we introduce a lightweight image captioning framework (I-Tuning), which contains a small number of trainable parameters.

Image Captioning Language Modelling

A Frustratingly Simple Approach for End-to-End Image Captioning

no code implementations30 Jan 2022 Ziyang Luo, Yadong Xi, Rongsheng Zhang, Jing Ma

Before training the captioning models, an extra object detector is utilized to recognize the objects in the image at first.

Image Captioning Object +1

Learning Fair Node Representations with Graph Counterfactual Fairness

1 code implementation10 Jan 2022 Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li

In this framework, we generate counterfactuals corresponding to perturbations on each node's and their neighbors' sensitive attributes.

Attribute counterfactual +2

Coarse-To-Fine Incremental Few-Shot Learning

1 code implementation24 Nov 2021 Xiang Xiang, Yuwen Tan, Qian Wan, Jing Ma

Such images form a new training set (i. e., support set) so that the incremental model is hoped to recognize a basenji (i. e., query) as a basenji next time.

Class Incremental Learning Few-Shot Learning +1

Malicious Mode Attack on EV Coordinated Charging Load and MIADRC Defense Strategy

no code implementations26 Oct 2021 Yichen Zhou, Weidong Liu, Jing Ma, Xinghao Zhen, Yonggang Li

Further, to mitigate the impact of MMA, a defense strategy based on multi-index information active disturbance rejection control is proposed to improve the stability and anti-disturbance ability of the power system, which considers the impact factors of both mode damping and disturbance compensation.

Analyzing the Implicit Position Encoding Ability of Transformer Decoder

no code implementations29 Sep 2021 Ziyang Luo, Yadong Xi, Jing Ma, Xiaoxi Mao, Changjie Fan

A common limitation of Transformer Encoder's self-attention mechanism is that it cannot automatically capture the information of word order, so one needs to feed the explicit position encodings into the target model.

Language Modelling Position

Communication Efficient Generalized Tensor Factorization for Decentralized Healthcare Networks

no code implementations3 Sep 2021 Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Sivasubramanium Bhavani, Joyce C. Ho

Tensor factorization has been proved as an efficient unsupervised learning approach for health data analysis, especially for computational phenotyping, where the high-dimensional Electronic Health Records (EHRs) with patients' history of medical procedures, medications, diagnosis, lab tests, etc., are converted to meaningful and interpretable medical concepts.

Computational Phenotyping

Temporal Network Embedding via Tensor Factorization

no code implementations22 Aug 2021 Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Joyce C. Ho

Representation learning on static graph-structured data has shown a significant impact on many real-world applications.

Link Prediction Network Embedding +1

Multi-objective optimization and explanation for stroke risk assessment in Shanxi province

no code implementations29 Jul 2021 Jing Ma, Yiyang Sun, Junjie Liu, Huaxiong Huang, Xiaoshuang Zhou, Shixin Xu

The experimental results showed that the QIDNN model with 7 interactive features achieve the state-of-art accuracy $83. 25\%$.

Federated Graph Classification over Non-IID Graphs

1 code implementation NeurIPS 2021 Han Xie, Jing Ma, Li Xiong, Carl Yang

Federated learning has emerged as an important paradigm for training machine learning models in different domains.

Clustering Dynamic Time Warping +4

Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US

1 code implementation29 May 2021 Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li

Besides, as the confounders may be time-varying during COVID-19 (e. g., vigilance of residents changes in the course of the pandemic), it is even more difficult to capture them.

Learning from Crowds by Modeling Common Confusions

2 code implementations24 Dec 2020 Zhendong Chu, Jing Ma, Hongning Wang

Crowdsourcing provides a practical way to obtain large amounts of labeled data at a low cost.

Image Classification

Debunking Rumors on Twitter with Tree Transformer

no code implementations COLING 2020 Jing Ma, Wei Gao

Rumors are manufactured with no respect for accuracy, but can circulate quickly and widely by {``}word-of-post{''} through social media conversations.

Transferable Multi-level Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multi-task Learning

no code implementations30 Jun 2020 Liqiang Lin, Qingqing Jia, Zheng Cheng, Yanyan Jiang, Yanwen Guo, Jing Ma

The development of efficient models for predicting specific properties through machine learning is of great importance for the innovation of chemistry and material science.

Drug Discovery Formation Energy +1

Spatio-Temporal Tensor Sketching via Adaptive Sampling

no code implementations21 Jun 2020 Jing Ma, Qiuchen Zhang, Joyce C. Ho, Li Xiong

In this paper, we propose SkeTenSmooth, a novel tensor factorization framework that uses adaptive sampling to compress the tensor in a temporally streaming fashion and preserves the underlying global structure.


Review-guided Helpful Answer Identification in E-commerce

1 code implementation13 Mar 2020 Wenxuan Zhang, Wai Lam, Yang Deng, Jing Ma

In this paper, we propose the Review-guided Answer Helpfulness Prediction (RAHP) model that not only considers the interactions between QA pairs but also investigates the opinion coherence between the answer and crowds' opinions reflected in the reviews, which is another important factor to identify helpful answers.

Answer Selection Community Question Answering

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis

no code implementations26 Aug 2019 Jing Ma, Qiuchen Zhang, Jian Lou, Joyce C. Ho, Li Xiong, Xiaoqian Jiang

We propose DPFact, a privacy-preserving collaborative tensor factorization method for computational phenotyping using EHR.

Computational Phenotyping Privacy Preserving

Sentence-Level Evidence Embedding for Claim Verification with Hierarchical Attention Networks

no code implementations ACL 2019 Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong

Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications.

Claim Verification Sentence

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