Weiqiang Jin

Weiqiang Jin

an Artificial Intelligence-related PhD Candidate at Xi'an Jiaotong University.

Posts by Collection

portfolio

Language Proficiencies

Chinese College English Test (CET) Level 4 and Level 6.


IELTS (International English Language Testing System) level 7.0. (TBD)

Competition Honors

The 17-th “HuaWei Cup” China Graduate Mathematical Modeling Competition.


Internet+ Innovation Competition.

School Honors

2023 Outstanding Xi’an Jiaotong University PhD Candidate.


2024 National Scholarship for PhD Students. (TBD)

publications

A Novel Cascade Model for End-to-End Aspect-Based Social Comment Sentiment Analysis

Published in the Special Issue Intelligent Implementations in the Digitalized Real World of Journal Electronics, 2022

This paper is about end-to-end aspect-based social comment sentiment analysis (E2E-ABSA) task.

Recommended citation: Hengbing Ding; Shan Huang; Weiqiang Jin; Yuan Shan; Hang Yu. (2022). "A Novel Cascade Model for End-to-End Aspect-Based Social Comment Sentiment Analysis." Electronics. 2022; 11(12):1810. https://doi.org/10.3390/electronics11121810

Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis

Published in Information Processing & Management (ipm), 2023

This paper is about Knowledge Enhancement on Aspect-based Sentiment Analysis (ABSA).

Recommended citation: Weiqiang Jin et al. (2023). "Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis." Information Processing & Management. Volume 60, Issue 3, 2023, 103260, ISSN 0306-4573. https://doi.org/10.1016/j.ipm.2022.103260

A semi-independent policies training method with shared representation for heterogeneous multi-agents reinforcement learning

Published in Frontiers in Neuroscience, 2023

This paper is about multi-agents reinforcement learning (MARL).

Recommended citation: Biao Zhao and Weiqiang Jin et al. (2023). "A semi-independent policies training method with shared representation for heterogeneous multi-agents reinforcement learning." Frontiers in Neuroscience. Volume 17, 2023, 1201370, ISSN 1662-453X. https://doi.org/10.3389/fnins.2023.1201370

Prompt learning for metonymy resolution: Enhancing performance with internal prior knowledge of pre-trained language models

Published in Knowledge-Based Systems, 2023

This paper is about the Prompt learning for metonymy resolution task.

Recommended citation: Biao Zhao and Weiqiang Jin et al. (2023). "Prompt learning for metonymy resolution: Enhancing performance with internal prior knowledge of pre-trained language models." Knowledge-Based Systems. Volume 279, 2023, 110928, ISSN 0950-7051. https://doi.org/10.1016/j.knosys.2023.110928

WordTransABSA: Enhancing Aspect-based Sentiment Analysis with masked language modeling for affective token prediction

Published in Expert Systems with Applications, 2023

This paper is about Aspect-based Sentiment Analysis (ABSA).

Recommended citation: Weiqiang Jin et al. (2023). "WordTransABSA: Enhancing Aspect-based Sentiment Analysis with masked language modeling for affective token prediction," Expert Systems with Applications. Volume 238, Part F, 2024, 122289, ISSN 0957-4174. https://doi.org/10.1016/j.eswa.2023.122289

Fintech Key-Phrase: A New Chinese Financial High-Tech Dataset Accelerating Expression-Level Information Retrieval

Published in ACM Transactions on Asian and Low-Resource Language Information Processing, 2023

This paper is about the Expression-Level Information Retrieval.

Recommended citation: Weiqiang Jin et al. (2023). "ACM Trans. Asian Low-Resour. Lang. Inf. Process. ACM Transactions on Asian and Low-Resource Language Information Processing " 22, 11, Article 253 (November 2023), 37 pages. https://dl.acm.org/doi/10.1145/3627989

Relation-aware graph structure embedding with co-contrastive learning for drug–drug interaction prediction

Published in Neurocomputing (neucom), 2024

This paper is about drug–drug interactions (DDIs).

Recommended citation: Mengying Jiang, Guizhong Liu, Biao Zhao, Yuanchao Su, Weiqiang Jin. (2023). "Relation-aware graph structure embedding with co-contrastive learning for drug–drug interaction prediction." Neurocomputing. Volume 572, 2024, 127203, ISSN 0925-2312. https://doi.org/10.1016/j.neucom.2023.127203

Hierarchical Multi-Relational Graph Representation Learning for Large-Scale Prediction of Drug-Drug Interactions

Published in IEEE Transactions on Big Data (tbd), 2024

This paper is about drug–drug interactions (DDIs).

Recommended citation: Mengying Jiang, Guizhong Liu, Yuanchao Su, Weiqiang Jin, Biao Zhao. (2024). "Hierarchical Multi-Relational Graph Representation Learning for Large-Scale Prediction of Drug-Drug Interactions." IEEE Transactions on Big Data. Volume , , , ISSN . https://doi.org/

Other suggested citation: Mengying Jiang, Guizhong Liu, Yuanchao Su, Weiqiang Jin, and Biao Zhao (2024). "Hierarchical Multi-Relational Graph Representation Learning for Large-Scale Prediction of Drug-Drug Interactions." arXiv preprint. arXiv:2402.18127.

Can Rumor Detection Enhance Fact Verification? Unraveling Cross-Task Synergies Between Rumor Detection and Fact Verification

Published in IEEE Transactions on Big Data (tbd), 2024

This paper is about few-shot fake news detection.

Recommended citation: W. Jin et al., "Can Rumor Detection Enhance Fact Verification? Unraveling Cross-Task Synergies Between Rumor Detection and Fact Verification," in IEEE Transactions on Big Data, doi: 10.1109/TBDATA.2024.3442555. https://doi.org/10.1109/TBDATA.2024.3442555

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A veracity dissemination consistency-based few-shot fake news detection framework by synergizing adversarial and contrastive self-supervised learning

Published in Scientific Reports, 2024

This paper is about few-shot fake news detection.

Recommended citation: Jin, W., Wang, N., Tao, T. et al. A veracity dissemination consistency-based few-shot fake news detection framework by synergizing adversarial and contrastive self-supervised learning. Sci Rep 14, 19470 (2024). https://doi.org/10.1038/s41598-024-70039-9

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Enhanced UAV Pursuit-Evasion Using Boids Modelling: A Synergistic Integration of Bird Swarm Intelligence and DRL

Published in CMC: Computers, Materials & Continua (CMC), 2024

This paper is about UAV pursuit-evasion controlling.

Recommended citation: Jin, W., Tian, X., Shi, B., Zhao, B., Duan, H., & Wu, H. (2024). Enhanced UAV pursuit-evasion using boids modelling: A synergistic integration of bird swarm intelligence and DRL. Computers, Materials & Continua, 2024, 055125, ISSN 1546-2226. https://doi.org/10.32604/cmc.2024.055125

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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.