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an up-to-date citation set of albert-jin's published works. thanks for citing~
Fintech Key-Phrase: A New Chinese Financial High-Tech Dataset Accelerating Expression-Level Information Retrieval
Citation Index: ⭐ ⭐ ⭐ ⭐ ⭐
https://dl.acm.org/doi/10.1145/3627989
Area: (Expression-Level Information Retrieval)
Journal: (ACM Transactions on Asian and Low-Resource Language Information Processing)
@article{10.1145/3627989,
author = {Jin, Weiqiang and Zhao, Biao and Zhang, Yu and Sun, Gege and Yu, Hang},
title = {Fintech Key-Phrase: A New Chinese Financial High-Tech Dataset Accelerating Expression-Level Information Retrieval},
year = {2023},
issue_date = {November 2023},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {22},
number = {11},
issn = {2375-4699},
url = {https://doi.org/10.1145/3627989},
doi = {10.1145/3627989},
journal = {ACM Trans. Asian Low-Resour. Lang. Inf. Process.},
month = {nov},
articleno = {253},
numpages = {37},
keywords = {ChatGPT-based data augment, Chinese management’s discussion and analysis, financial high technology field, expression-level information extraction, Information retrieval}
}
WordTransABSA: Enhancing Aspect-based Sentiment Analysis with masked language modeling for affective token prediction
Citation Index: ⭐ ⭐ ⭐ ⭐
https://doi.org/10.1016/j.eswa.2023.122289
https://www.sciencedirect.com/science/article/abs/pii/S0957417423027914
Area: (Aspect-based Sentiment Analysis)
Journal: (ESWA)
@article{JIN2024122289,
title = {WordTransABSA: Enhancing Aspect-based Sentiment Analysis with masked language modeling for affective token prediction},
journal = {Expert Systems with Applications},
volume = {238},
pages = {122289},
year = {2024},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2023.122289},
url = {https://www.sciencedirect.com/science/article/pii/S0957417423027914},
author = {Weiqiang Jin and Biao Zhao and Yu Zhang and Jia Huang and Hang Yu},
keywords = {Natural Language Processing, Aspect-based Sentiment Analysis, Masked Language Model, Pre-trained Language Model, Few-shot supervised learning},
}
Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis 😃 😃
Citation Index: ⭐ ⭐ ⭐ ⭐
https://doi.org/10.1016/j.ipm.2022.103260
https://www.sciencedirect.com/science/article/pii/S0306457322003612
Area: ABSA (ASC)
Journal: (IP&M)
@article{JIN2023103260,
title = {Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis},
journal = {Information Processing & Management},
volume = {60},
number = {3},
pages = {103260},
year = {2023},
issn = {0306-4573},
doi = {https://doi.org/10.1016/j.ipm.2022.103260},
url = {https://www.sciencedirect.com/science/article/pii/S0306457322003612},
author = {Weiqiang Jin and Biao Zhao and Liwen Zhang and Chenxing Liu and Hang Yu},
}
Prompt learning for metonymy resolution: Enhancing performance with internal prior knowledge of pre-trained language models (共同一作)
Citation Index: ⭐ ⭐ ⭐ ⭐
https://doi.org/10.1016/j.knosys.2023.110928
https://www.sciencedirect.com/science/article/pii/S0950705123006780
Area: (Prompt learning)
Journal: (KBS)
@article{ZHAO2023110928,
title = {Prompt learning for metonymy resolution: Enhancing performance with internal prior knowledge of pre-trained language models},
journal = {Knowledge-Based Systems},
volume = {279},
pages = {110928},
year = {2023},
issn = {0950-7051},
doi = {https://doi.org/10.1016/j.knosys.2023.110928},
url = {https://www.sciencedirect.com/science/article/pii/S0950705123006780},
author = {Biao Zhao and Weiqiang Jin and Yu Zhang and Subin Huang and Guang Yang},
keywords = {Metonymy resolution, Prompt learning, Pre-trained language model, Prompting template engineering, Answer engineering},
}
Using Masked Language Modeling to Enhance BERT-Based Aspect-Based Sentiment Analysis for Affective Token Prediction
Citation Index: ⭐ ⭐ ⭐
https://doi.org/10.1007/978-3-031-44204-9_44
https://link.springer.com/chapter/10.1007/978-3-031-44204-9_44
Area: (Aspect-Based Sentiment Analysis)
Conference: (ICANN)
@InProceedings{10.1007/978-3-031-44204-9_44,
author="Jin, Weiqiang
and Zhao, Biao
and Liu, Chenxing
and Zhang, Heng
and Jiang, Mengying",
editor="Iliadis, Lazaros
and Papaleonidas, Antonios
and Angelov, Plamen
and Jayne, Chrisina",
title="Using Masked Language Modeling to Enhance BERT-Based Aspect-Based Sentiment Analysis for Affective Token Prediction",
booktitle="Artificial Neural Networks and Machine Learning -- ICANN 2023",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="530--542",
isbn="978-3-031-44204-9"
}
Exploring the Capability of ChatGPT for Cross-Linguistic Agricultural Document Classification: Investigation and Evaluation
Citation Index: ⭐ ⭐ ⭐
https://link.springer.com/chapter/10.1007/978-981-99-8145-8_18
Area: (Document Classification)
Conference: (ICONIP)
@InProceedings{10.1007/978-981-99-8145-8_18,
author="Jin, Weiqiang
and Zhao, Biao
and Liu, Guizhong",
editor="Luo, Biao
and Cheng, Long
and Wu, Zheng-Guang
and Li, Hongyi
and Li, Chaojie",
title="Exploring the Capability of ChatGPT for Cross-Linguistic Agricultural Document Classification: Investigation and Evaluation",
booktitle="Neural Information Processing",
year="2024",
publisher="Springer Nature Singapore",
address="Singapore",
pages="220--237",
isbn="978-981-99-8145-8"
}
ChatAgri: Exploring Potentials of ChatGPT on Cross-linguistic Agricultural Text Classification (共同一作)
Citation Index: ⭐ ⭐ ⭐
https://doi.org/10.1016/j.neucom.2023.126708
https://www.sciencedirect.com/science/article/pii/S0925231223008317
Area: (Agricultural Text Classification)
Journal: (Neurocomputing)
@article{ZHAO2023126708,
title = {ChatAgri: Exploring potentials of ChatGPT on cross-linguistic agricultural text classification},
journal = {Neurocomputing},
volume = {557},
pages = {126708},
year = {2023},
issn = {0925-2312},
doi = {https://doi.org/10.1016/j.neucom.2023.126708},
url = {https://www.sciencedirect.com/science/article/pii/S0925231223008317},
author = {Biao Zhao and Weiqiang Jin and Javier {Del Ser} and Guang Yang},
keywords = {Agricultural text classification, Very large pre-trained language model, Generative Pre-trained Transformer (GPT), ChatGPT, GPT-4},
}
@misc{zhao2023chatagri,
title={ChatAgri: Exploring Potentials of ChatGPT on Cross-linguistic Agricultural Text Classification},
author={Biao Zhao and Weiqiang Jin and Javier Del Ser and Guang Yang},
year={2023},
eprint={2305.15024},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
A semi-independent policies training method with shared representation for heterogeneous multi-agents reinforcement learning (共同一作)
Citation Index: ⭐ ⭐ ⭐
https://doi.org/10.3389/fnins.2023.1201370
https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1201370/full
Area: (Reinforcement Learning)
Journal: (Frontiers in Neuroscience)
@ARTICLE{10.3389/fnins.2023.1201370,
AUTHOR={Zhao, Biao and Jin, Weiqiang and Chen, Zhang and Guo, Yucheng },
TITLE={A semi-independent policies training method with shared representation for heterogeneous multi-agents reinforcement learning},
JOURNAL={Frontiers in Neuroscience},
VOLUME={17},
YEAR={2023},
URL={https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1201370},
DOI={10.3389/fnins.2023.1201370},
ISSN={1662-453X},
Fintech Key-Phrase: A New Chinese Financial High-Tech Dataset Accelerating Expression-Level Information Retrieval
Citation Index: ⭐ ⭐ ⭐ ⭐
https://doi.org/10.1007/978-3-031-30675-4_31
https://link.springer.com/chapter/10.1007/978-3-031-30675-4_31
Area: (Information Retrieval)
Conference: (DASFAA)
@InProceedings{10.1007/978-3-031-30675-4_31,
author="Jin, Weiqiang
and Zhao, Biao
and Liu, Chenxing",
editor="Wang, Xin
and Sapino, Maria Luisa
and Han, Wook-Shin
and El Abbadi, Amr
and Dobbie, Gill
and Feng, Zhiyong
and Shao, Yingxiao
and Yin, Hongzhi",
title="Fintech Key-Phrase: A New Chinese Financial High-Tech Dataset Accelerating Expression-Level Information Retrieval",
booktitle="Database Systems for Advanced Applications",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="425--440",
isbn="978-3-031-30675-4"
}
Improving embedded knowledge graph multi-hop question answering by introducing relational chain reasoning 😃
Citation Index: ⭐ ⭐ ⭐ ⭐
https://link.springer.com/article/10.1007/s10618-022-00891-8
https://link.springer.com/content/pdf/10.1007/s10618-022-00891-8.pdf
Area: KGQA
Journal: (DMKD)
@Article{jwq2022rcekgqa,
author={Jin, Weiqiang
and Zhao, Biao
and Yu, Hang
and Tao, Xi
and Yin, Ruiping
and Liu, Guizhong},
title={Improving embedded knowledge graph multi-hop question answering by introducing relational chain reasoning},
journal={Data Mining and Knowledge Discovery},
year={2022},
month={Nov},
day={11},
issn={1573-756X},
doi={10.1007/s10618-022-00891-8},
url={https://doi.org/10.1007/s10618-022-00891-8}
}
Citation Index: ⭐ ⭐
https://ieeexplore.ieee.org/document/9643376
2021 IEEE 33rd International Conference on Tools for Artificial Intelligence (ICTAI)
Area: Object Detection
Conference: (ICTAI)
@INPROCEEDINGS{9643376,
author={Jin, Weiqiang and Yu, Hang and Luo, Xiangfeng},
booktitle={2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)},
title={CvT-ASSD: Convolutional vision-Transformer Based Attentive Single Shot MultiBox Detector},
year={2021},
volume={},
number={},
pages={736-744},
doi={10.1109/ICTAI52525.2021.00117}
}
Citation Index: ⭐
https://www.mdpi.com/2079-9292/11/12/1810
Area: Aspect-Based Sentiment Analysis
Journal: (Electronics)
@Article{electronics11121810,
AUTHOR = {Ding, Hengbing and Huang, Shan and Jin, Weiqiang and Shan, Yuan and Yu, Hang},
TITLE = {A Novel Cascade Model for End-to-End Aspect-Based Social Comment Sentiment Analysis},
JOURNAL = {Electronics},
VOLUME = {11},
YEAR = {2022},
NUMBER = {12},
ARTICLE-NUMBER = {1810},
URL = {https://www.mdpi.com/2079-9292/11/12/1810},
ISSN = {2079-9292},
DOI = {10.3390/electronics11121810},
}
Relation-aware graph structure embedding with co-contrastive learning for drug–drug interaction prediction (四作)
@article{JIANG2024127203,
title = {Relation-aware graph structure embedding with co-contrastive learning for drug–drug interaction prediction},
journal = {Neurocomputing},
volume = {572},
pages = {127203},
year = {2024},
issn = {0925-2312},
doi = {https://doi.org/10.1016/j.neucom.2023.127203},
url = {https://www.sciencedirect.com/science/article/pii/S0925231223013267},
author = {Mengying Jiang and Guizhong Liu and Biao Zhao and Yuanchao Su and Weiqiang Jin},
keywords = {Adverse drug reactions, Graph neural networks, Graph structure embedding, Self-supervised learning},
}
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