BertGCN: Transductive Text Classification by Combining GNN and BERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1423 · Cited by 48,293 · see citing works

Statistical Learning Theory

Wu, Y., & Vapnik, V. N. (1999) · Technometrics · doi:10.2307/1271368 · Cited by 27,236 · see citing works

Semi-supervised classification with graph convolutional networks

Kipf, T. N., & Welling, M. (2016) · arXiv · doi:10.48550/arxiv.1609.02907 · Cited by 24,853 · see citing works

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019) · arXiv · doi:10.48550/arxiv.1907.11692 · Cited by 16,515 · see citing works

Convolutional Neural Networks for Sentence Classification

Kim, Y. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1181 · Cited by 14,831 · see citing works

Momentum Contrast for Unsupervised Visual Representation Learning

He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00975 · Cited by 13,347 · see citing works

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reimers, N., & Gurevych, I. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1410 · Cited by 12,778 · see citing works

Graph Attention Networks

Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., & Bengio, Y. (2017) · arXiv · doi:10.48550/arxiv.1710.10903 · Cited by 12,107

Graph Attention NetworksPreprint

Veličković, P., Casanova, A., Liò, P., Cucurull, G., Romero, A., & Bengio, Y. (2017) · arXiv (Cornell University) · doi:10.17863/cam.48429 · Cited by 12,099 · see citing works

Inductive Representation Learning on Large Graphs

Hamilton, W. L., Ying, R., & Leskovec, J. (2017) · arXiv · doi:10.48550/arxiv.1706.02216 · Cited by 10,639 · see citing works

The graph neural network model

Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M., & Monfardini, G. (2009) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2008.2005605 · Cited by 9,582 · see citing works

Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting

Yu, T., Yin, H.-T., & Zhu, Z.-X. (2017) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/505 · Cited by 5,695 · see citing works

Formal Semantics for Kolmogorov-Arnold Network Representations of Operational GamesPreprint

Xu, K., Hu, W., Leskovec, J., & Jegelka, S. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1810.00826 · Cited by 5,266 · see citing works

Unsupervised Feature Learning via Non-parametric Instance Discrimination

Wu, Z., Xiong, Y., Yu, S. X., & Lin, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00393 · Cited by 3,664 · see citing works

Variational Graph Auto-EncodersPreprint

Kipf, T., & Welling, M. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1611.07308 · Cited by 3,635 · see citing works

A Comprehensive Survey on Graph Neural Networks

Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., & Yu, P. (2020) · UTS ePRESS (University of Technology Sydney) · Cited by 3,174 · see citing works

Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning

Li, Q., Han, Z., & Wu, X.-M. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11604 · Cited by 2,872 · see citing works

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic ForecastingPreprint

Li, Y., Yu, R., Shahabi, C., & Liu, Y. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.01926 · Cited by 2,597 · see citing works

Simplifying Graph Convolutional NetworksPreprint

Wu, F., Zhang, T., Junior, A. H. D. S., Fifty, C., Yu, T., & Weinberger, K. Q. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.07153 · Cited by 2,251 · see citing works

Graph Convolutional Networks for Text Classification

Yao, L., Mao, C., & Luo, Y. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33017370 · Cited by 2,171 · see citing works

Seeing stars

Pang, B., & Lee, L. (2005) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.3115/1219840.1219855 · Cited by 2,153 · see citing works

Deep Neural Networks for Learning Graph Representations

Cao, S., Lu, W., & Xu, Q. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10179 · Cited by 1,070 · see citing works

Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

Marcheggiani, D., & Titov, I. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d17-1159 · Cited by 907 · see citing works

PTE

Tang, J., Qu, M., & Mei, Q. (2015) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2783258.2783307 · Cited by 814 · see citing works

Graph Convolution over Pruned Dependency Trees Improves Relation Extraction

Zhang, Y., Qi, P., & Manning, C. D. (2018) · Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1244 · Cited by 809 · see citing works

Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scalesPreprint

Pang, B., & Lee, L. (2005) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0506075 · Cited by 744 · see citing works

A C-LSTM Neural Network for Text ClassificationPreprint

Zhou, C., Sun, C., Liu, Z., & Lau, F. C. M. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.08630 · Cited by 666 · see citing works

GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal GraphsPreprint

Zhang, J., Shi, X., Xie, J., Ma, H., King, I., & Yeung, D. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.07294 · Cited by 580 · see citing works

Geometric Matrix Completion with Recurrent Multi-Graph Neural NetworksPreprint

Monti, F., Bronstein, M., & Bresson, X. (2017) · Neural Information Processing Systems · doi:10.48550/arxiv.1704.06803 · Cited by 558 · see citing works

DON’T FOLLOW ME - Spam Detection in Twitter

Wang, A. H. (2010) · International Conference on Security and Cryptography · doi:10.5220/0002996201420151 · Cited by 469 · see citing works

Joint Embedding of Words and Labels for Text Classification

Wang, G., Li, C., Wang, W., Zhang, Y., Shen, D., Zhang, X., Henao, R., & Carin, L. (2018) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p18-1216 · Cited by 461 · see citing works

Learning Deep Generative Models of GraphsPreprint

Li, Y., Vinyals, O., Dyer, C., Pascanu, R., & Battaglia, P. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.03324 · Cited by 445 · see citing works

MolGAN: An implicit generative model for small molecular graphs

De Cao, N., & Kipf, T. (2018) · arXiv · doi:10.48550/arxiv.1805.11973 · Cited by 442 · see citing works

Text Level Graph Neural Network for Text Classification

Huang, L., Ma, D., Li, S., Zhang, X., & Wang, H. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1345 · Cited by 338 · see citing works

Tensor Graph Convolutional Networks for Text Classification

Liu, X., You, X., Zhang, X., Wu, J. Y., & Lv, P. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i05.6359 · Cited by 299 · see citing works

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

Monti, F., Bronstein, M. M., & Bresson, X. (2017) · neural information processing systems · Cited by 232 · see citing works

VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification

Lu, Z., Du, P., & Nie, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-45439-5_25 · Cited by 157 · see citing works

Opinion mining and sentiment analysis

Bakshi, R. K., Kaur, N., Kaur, R., & Kaur, G. (2016) · International Conference on Computing for Sustainable Global Development · Cited by 154 · see citing works

Opinion Mining and Sentiment Analysis

Zhai, C., & Massung, S. (2016) · doi:10.1145/2915031.2915050 · Cited by 86 · see citing works

Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural NetworksPreprint

Song, L., Wang, Z., Yu, M., Zhang, Y., Florian, R., & Gildea, D. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.02040 · Cited by 82 · see citing works

GILE: A Generalized Input-Label Embedding for Text Classification

Pappas, N., & Henderson, J. (2019) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00259 · Cited by 81 · see citing works

Zero-shot Text Classification via Reinforced Self-training

Ye, Z., Geng, Y., Chen, J., Chen, J., Xu, X., Zheng, S., Wang, F., Zhang, J., & Chen, H. (2020) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2020.acl-main.272 · Cited by 79 · see citing works

Text Graph Transformer for Document Classification

Zhang, H., & Zhang, J. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.668 · Cited by 67 · see citing works

Uncertainty-aware Self-training for Text Classification with Few LabelsPreprint

Mukherjee, S., & Awadallah, A. H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.15315 · Cited by 50 · see citing works

Description Based Text Classification with Reinforcement LearningPreprint

Chai, D., Wu, W., Han, Q., Wu, F. Q., & Li, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.03067 · Cited by 45 · see citing works

Comprehensive Information Integration Modeling Framework for Video Titling

Zhang, S., Tan, Z., Zhao, Z., Yu, J., Kuang, K., Jiang, T., Zhou, J.-R., Yang, H.-X., & Wu, F. (2020) · Knowledge Discovery and Data Mining · doi:10.1145/3394486.3403325 · Cited by 40 · see citing works

Enhancing Generalization in Natural Language Inference by Syntax

He, Q., Wang, H., & Zhang, Y. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.447 · Cited by 13 · see citing works

Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories

Chen, T., Wang, Z., Li, L., Li, D., Li, Z., Chang, X., Bian, P., Liang, G., Wang, Q., & Xie, T. (2025) · Schloss Dagstuhl – Leibniz-Zentrum für Informatik · doi:10.4230/lipics.ecoop.2025.6

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805

Pre-Trained Language Models and Their Applications

Wang, H., Li, J., Wu, H. R., Hovy, E. H., & Sun, Y. (2022) · Engineering · doi:10.1016/j.eng.2022.04.024 · Cited by 404 · see citing works

A Survey on Text Classification Algorithms: From Text to Predictions

Gasparetto, A., Marcuzzo, M., Zangari, A., & Albarelli, A. (2022) · Information · doi:10.3390/info13020083 · Cited by 278 · see citing works

DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis

Wang, R., Jiang, Y., Jin, J., Yin, C., Yu, H., Wang, F., Feng, J., Su, R., Nakai, K., Zou, Q., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad055 · Cited by 177 · see citing works

CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation

Zhang, S., Yao, D., Zhao, Z., Chua, T.-S., & Wu, F. (2021) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3404835.3462908 · Cited by 141 · see citing works

Hierarchical graph-based text classification framework with contextual node embedding and BERT-based dynamic fusion

Onan, A. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101610 · Cited by 99 · see citing works

Graph neural networks for text classification: a survey

Wang, K., Ding, Y., & Han, S. C. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10808-0 · Cited by 99 · see citing works

InducT-GCN: Inductive Graph Convolutional Networks for Text Classification

Wang, K., Han, S. C., & Poon, J. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956075 · Cited by 68 · see citing works

Long short-term memory with activation on gradient

Qin, C., Chen, L., Cai, Z., Liu, M., & Jin, L. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.04.026 · Cited by 62 · see citing works

Text FCG: Fusing Contextual Information via Graph Learning for text classification

Wang, Y., Wang, C., Zhan, J., Ma, W., & Jiang, Y. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119658 · Cited by 52 · see citing works

Infusing Knowledge from Wikipedia to Enhance Stance Detection

He, Z., Mokhberian, N., & Lerman, K. (2022) · Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA) · doi:10.18653/v1/2022.wassa-1.7 · Cited by 52 · see citing works

Relational Graph Convolutional Network for Text-Mining-Based Accident Causal Classification

Chen, Z., Huang, K., Li, W., Zhong, Z., & Jiao, Z. (2022) · Applied Sciences · doi:10.3390/app12052482 · Cited by 35 · see citing works

Re-examining lexical and semantic attention: Dual-view graph convolutions enhanced BERT for academic paper rating

Xue, Z., He, G., Liu, J., Jiang, Z., Zhao, S. X., & Lu, W. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103216 · Cited by 33 · see citing works

Joint Learning With BERT-GCN and Multi-Attention for Event Text Classification and Event Assignment

She, X., Chen, J., & Chen, G. (2022) · IEEE Access · doi:10.1109/access.2022.3156918 · Cited by 32 · see citing works

Graph neural network–driven text classification for fire-door defect inspection in pre-completion construction

Wang, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-28120-4 · Cited by 27 · see citing works

Transformer and Graph Convolutional Network for Text Classification

Liu, B., Guan, W., Yang, C., Fang, Z., & Lu, Z. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00337-z · Cited by 29 · see citing works

Hierarchical Graph Convolutional Networks for Structured Long Document Classification

Liu, T., Hu, Y., Wang, B., Sun, Y., Gao, J., & Yin, B. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3185295 · Cited by 23 · see citing works

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

Wang, G., Lou, X., Guo, F., Kwok, D., & Cao, C. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3346210 · Cited by 23 · see citing works

Text Classification Using Graph Convolutional Networks: A Comprehensive Survey

Rizvi, S. M. H., Imran, R., & Mahmood, A. (2025) · ACM Computing Surveys · doi:10.1145/3714456 · Cited by 28 · see citing works

Contrastive learning from label distribution: A case study on text classification

Tao, Q., Li, F., Zhang, M., Jin, G., Fan, P., & Dai, W. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.07.076 · Cited by 21 · see citing works

Contrastive multi-graph learning with neighbor hierarchical sifting for semi-supervised text classification

Ai, W., Li, J., Wang, Z., Wei, Y., Meng, T., & Li, K. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125952 · Cited by 21 · see citing works

A Systematic Survey of Graph Convolutional Networks for Artificial Intelligence Applications

Sadasivan, A., Gananathan, K., Dhanith, P. R. J., & Surendiran, B. (2025) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70012 · Cited by 21 · see citing works

Technology-Assisted Motivational Interviewing: Developing a Scalable Framework for Promoting Engagement with Tobacco Cessation Using NLP and Machine Learning

Saiyed, A., Layton, J. F., Borsari, B. E., Cheng, J., Kanzaveli, T., Tsvetovat, M., & Satterfield, J. M. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.09.091 · Cited by 20 · see citing works

Predictive End-to-End Enterprise Process Network Monitoring

Oberdorf, F., Schaschek, M., Weinzierl, S., Stein, N., Matzner, M., & Flath, C. M. (2022) · Business & Information Systems Engineering · doi:10.1007/s12599-022-00778-4 · Cited by 20 · see citing works

Zero-Shot and Few-Shot Stance Detection on Varied Topics via Conditional Generation

Wen, H., & Hauptmann, A. G. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-short.127 · Cited by 20 · see citing works

A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications

Li, X., Zhang, Y., Jin, J., Sun, F., Li, N., & Liang, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282824 · Cited by 19 · see citing works

A Multimodal Framework for the Identification of Vaccine Critical Memes on Twitter

Naseem, U., Kim, J., Khushi, M., & Dunn, A. G. (2023) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3539597.3570450 · Cited by 18 · see citing works

Chain-of-Thought Embeddings for Stance Detection on Social Media

Gatto, J., Sharif, O., & Preum, S. M. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.273 · Cited by 18 · see citing works

A Heterogeneous Directed Graph Attention Network for inductive text classification using multilevel semantic embeddings

Lin, M., Wang, T., Zhu, Y., Li, X., Zhou, X., & Wang, W. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111797 · Cited by 18 · see citing works

A distributable German clinical corpus containing cardiovascular clinical routine doctor’s letters

Richter-Pechanski, P., Wiesenbach, P., Schwab, D. M., Kiriakou, C., He, M., Allers, M. M., Tiefenbacher, A. S., Kunz, N., Martynova, A., Spiller, N., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02128-9 · Cited by 16 · see citing works

Simplified-Boosting Ensemble Convolutional Network for Text Classification

Zeng, F., Chen, N., Yang, D., & Meng, Z. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-10843-4 · Cited by 15 · see citing works

Combining transformer-based model and GCN to predict ICD codes from clinical records

Lu, P., & Xue, J. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.111113 · Cited by 14 · see citing works

Bert-based graph unlinked embedding for sentiment analysis

Jin, Y., & Zhao, A. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01289-9 · Cited by 14 · see citing works

Graph Receptive Transformer Encoder for Text Classification

Aras, A. C., Alikaşifoğlu, T., & Koç, A. (2024) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2024.3380362 · Cited by 14 · see citing works

Collaborative Knowledge Infusion for Low-Resource Stance Detection

Yan, M., Joey, T. Z., & Ivor, W. T. (2024) · Big Data Mining and Analytics · doi:10.26599/bdma.2024.9020021 · Cited by 14 · see citing works

MonaCoBERT: Monotonic Attention Based ConvBERT for Knowledge Tracing

Lee, U., Park, Y., Kim, Y., Choi, S., & Kim, H. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-63031-6_10 · Cited by 14 · see citing works

Case reports unlocked: Harnessing large language models to advance research on child maltreatment

Stoll, D., Wehrli, S., & Lätsch, D. (2024) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2024.107202 · Cited by 14 · see citing works

BERT-GraphSAGE: hybrid approach to spam detection

Zouak, F., Beqqali, O. E., & Riffi, J. (2025) · Journal Of Big Data · doi:10.1186/s40537-025-01176-9 · Cited by 14 · see citing works

Penetrating the Hostile: Detecting DeFi Protocol Exploits Through Cross-Contract Analysis

Li, X., Li, W., Liu, Z., Zhang, Y., & Mao, Y. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3626979 · Cited by 14 · see citing works

Transformers are Short-Text Classifiers

Karl, F., & Scherp, A. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-40837-3_7 · Cited by 15 · see citing works

CoGraphNet for enhanced text classification using word-sentence heterogeneous graph representations and improved interpretability

Li, P., Fu, X., Chen, J., & Hu, J. (2025) · Scientific Reports · doi:10.1038/s41598-024-83535-9 · Cited by 13 · see citing works

Contextualized Graph Embeddings for Adverse Drug Event Detection

Gao, Y., Ji, S., Zhang, T., Tiwari, P., & Marttinen, P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26390-3_35 · Cited by 12 · see citing works

Credit Scoring Prediction Using Deep Learning Models in the Financial Sector

Shi, X., Tang, D., & Yu, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3591005 · Cited by 12 · see citing works

DTFL: A Digital Twin-Assisted Graph Neural Network Approach for Service Function Chains Failure Localization

Guo, K., Chen, J., Dong, P., Zou, T., Zhu, J., Huang, X., Liu, S., & Liao, C. (2023) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2023.3294506 · Cited by 10 · see citing works

Dual-channel knowledge attention for traditional Chinese medicine syndrome differentiation

Liu, B., Huang, H., Liu, X., Zhao, J., & Mo, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-96404-w · Cited by 10 · see citing works

TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique

Waqas, M. M., Zhang, F., Laghari, A. A., Almadhor, A. S., Petrinec, F., Iqbal, A., & Khalil, M. M. Y. (2025) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-025-00792-w · Cited by 9 · see citing works

LMCBert: An Automatic Academic Paper Rating Model Based on Large Language Models and Contrastive Learning

Liu, C., Zhang, X., Zhao, H., Liu, Z., Xi, X., & Yu, L. (2025) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2025.3550203 · Cited by 10 · see citing works

Detecting sarcasm in user-generated content integrating transformers and gated graph neural networks

Qin, Z., Luo, Q., Zang, Z., & Fu, H. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.2817 · Cited by 10 · see citing works

Attack Behavior Extraction Based on Heterogeneous Cyberthreat Intelligence and Graph Convolutional Networks

Tang, B., Wang, J., Qiu, H., Yu, J., Yu, Z., & Liu, S. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.029135 · Cited by 10 · see citing works

TextGCL: Graph Contrastive Learning for Transductive Text Classification

Zhao, Y., & Song, X. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191923 · Cited by 9 · see citing works

A novel model for relation prediction in knowledge graphs exploiting semantic and structural feature integration

Yang, J., Lu, G., He, S., Cao, Q., & Liu, Y. (2024) · Scientific Reports · doi:10.1038/s41598-024-63279-2 · Cited by 9 · see citing works

An effective multi-modal adaptive contextual feature information fusion method for Chinese long text classification

Xu, Y., Liu, G., Zhang, L., Shen, X., & Luo, S. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10835-x · Cited by 8 · see citing works

Software bug prediction using graph neural networks and graph-based text representations

Siachos, I., Kanakaris, N., & Karacapilidis, N. I. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125290 · Cited by 11 · see citing works

GazeGCN: Gaze-aware Graph Convolutional Network for Text Classification

Wang, B., Liang, B., Bai, Z., Yang, M., Gui, L., & Xu, R. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128680 · Cited by 9 · see citing works

Graph-aware pre-trained language model for political sentiment analysis in Filipino social media

Aquino, J. A., Liew, D.-J., & Chang, Y. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110317 · Cited by 10 · see citing works

Leveraging large language models for sentiment analysis: A hybrid contextual and linguistic feature fusion approach

Pha, L. A., & Tran, T. K. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110643 · Cited by 8 · see citing works

PepGraphormer: an ESM-GAT hybrid deep learning framework for antimicrobial peptide prediction

Lin, C., Xiong, S., Li, J., Cui, F., Zhang, Z., Shi, H., & Wei, L. (2026) · Journal of Cheminformatics · doi:10.1186/s13321-025-01144-8 · Cited by 8 · see citing works

Continual Graph Convolutional Network for Text Classification

Wu, T., Liu, Q., Cao, Y., Huang, Y. T., Wu, X.-M., & Ding, J. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i11.26611 · Cited by 8 · see citing works

Knowledge-Graph- and GCN-Based Domain Chinese Long Text Classification Method

Wang, Y., Wang, Y., Hu, H., Zhou, S., & Wang, Q. (2023) · Applied Sciences · doi:10.3390/app13137915 · Cited by 8 · see citing works

TGCN-Bert Emoji Prediction in Information Systems Using TCN and GCN Fusing Features Based on BERT

Yang, Z., Xia, Y., & Xu, H. (2023) · International Journal on Semantic Web and Information Systems · doi:10.4018/ijswis.331082 · Cited by 8 · see citing works

Aggregating Local and Global Text Features for Linguistic Steganalysis

Xiang, L., Liu, Y., You, H., & Ou, C. (2022) · IEEE Signal Processing Letters · doi:10.1109/lsp.2022.3185946 · Cited by 8 · see citing works

A Text Classification Method Based on BERT-Att-TextCNN Model

Zhang, H., Shan, Y., Jiang, P., & Cai, X. (2022) · IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) · doi:10.1109/imcec55388.2022.10019808 · Cited by 8 · see citing works

TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings

Hanley, H. W. A., & Durumeric, Z. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.694 · Cited by 9 · see citing works

AHCL-TC: Adaptive Hypergraph Contrastive Learning Networks for Text Classification

Zhang, Z., Ni, H., Jia, X., Su, F., Liu, M., Yun, W., & Wu, G. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127989 · Cited by 8 · see citing works

A hybrid re-fusion model for text classification

Liu, Q., Xiao, K., & Qian, Z. (2025) · Scientific Reports · doi:10.1038/s41598-025-90864-w · Cited by 7 · see citing works

Text Classification Using Deep Learning Methods

Zhang, C. (2022) · IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) · doi:10.1109/tocs56154.2022.10015956 · Cited by 7 · see citing works

Mal-Bert-GCN: Malware Detection by Combining Bert and GCN

Ding, Z., Xu, H., Guo, Y., Yan, L., Cui, L., & Hao, Z. (2022) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom56396.2022.00034 · Cited by 8 · see citing works

Graph learning and its advancements on large language models: A holistic survey

Wei, S., Wang, J., Zhao, Y., Chen, X., Hu, X., Li, Q., Zhuang, F., Ren, F., & Kou, G. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132396 · Cited by 7 · see citing works

Classification of Research Papers on Radio Frequency Electromagnetic Field (RF-EMF) Using Graph Neural Networks (GNN)

Jang, Y., Won, K., Choi, H., & Shin, S. Y. (2023) · Applied Sciences · doi:10.3390/app13074614 · Cited by 7 · see citing works

scGraPhT: Merging Transformers and Graph Neural Networks for Single-Cell Annotation

Koç, E., Kulkul, E., Kaynar, G., Çukur, T., Açar, M., & Koç, A. (2025) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2025.3573591 · Cited by 6 · see citing works

Medical Graph Diffusion: Hybrid Graph Diffusion With Heterogeneous Graph Convolutional Networks for Medical Text Classification

Wang, G., Li, S., Liu, K., Hu, X., & Cao, C. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3576247 · Cited by 6 · see citing works

A dynamic graph structural framework for implicit sentiment identification based on complementary semantic and structural information

Zhao, Y., Mamat, M., Aysa, A., & Ubul, K. (2024) · Scientific Reports · doi:10.1038/s41598-024-62269-8 · Cited by 6 · see citing works

DA-BAG: A multi-model fusion text classification method combining BERT and GCN using self-domain adversarial training

Shao, D., Su, S.-C., Ma, L., Yi, S., & Lai, H. (2024) · Journal of Intelligent Information Systems · doi:10.1007/s10844-024-00889-2 · Cited by 6 · see citing works

A parameter-free text classification method based on dual compressors

Mao, Y., Ding, Y., & Cui, T. (2025) · Knowledge and Information Systems · doi:10.1007/s10115-024-02335-9 · Cited by 6 · see citing works

An Intelligent system for the categorization of question time official documents of the Italian Chamber of Deputies

Cavalieri, A., Ducange, P., Fabi, S., Russo, F., & Tonellotto, N. (2022) · Journal of Information Technology & Politics · doi:10.1080/19331681.2022.2082622 · Cited by 6 · see citing works

DCAT: Combining Multisemantic Dual-Channel Attention Fusion for Text Classification

Dong, K., Liu, Y., Xu, F., & Liu, P. (2023) · IEEE Intelligent Systems · doi:10.1109/mis.2023.3268228 · Cited by 7 · see citing works

Knowledge Graph Completion with Triple Structure and Text Representation

Liu, S., Qin, Y., Xu, M., & Kolmanič, S. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00271-0 · Cited by 6 · see citing works

DeFiTail: DeFi Protocol Inspection through Cross-Contract Execution Analysis

Li, W., Li, X., Zhang, Y., & Li, Z. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589335.3651488 · Cited by 6 · see citing works

Learning label smoothing for text classification

Ren, H. Y., Zhao, Y., Zhang, Y., & Sun, W. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2005 · Cited by 6 · see citing works

GNN-encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval

Liu, J., Liu, J., Yang, Y., Wang, J., Wu, W., Zhao, D., & Yan, R. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.39 · Cited by 8 · see citing works

Text-RGNNs: Relational Modeling for Heterogeneous Text Graphs

Aras, A. C., Alikaşifoğlu, T., & Koç, A. (2024) · IEEE Signal Processing Letters · doi:10.1109/lsp.2024.3433568 · Cited by 5 · see citing works

Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection

Hu, K., Yan, M., Chong, W.-H., Yap, Y. K., Guan, C., Zhou, J. T., & Tsang, I. W.-H. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650428 · Cited by 5 · see citing works

Relationship extraction between entities with long distance dependencies and noise based on semantic and syntactic features

Wang, L., Wu, F. Q., Liu, X., Cao, J., Ma, M., & Qu, Z. (2025) · Scientific Reports · doi:10.1038/s41598-025-00915-5 · Cited by 5 · see citing works

Advancing minority stress detection with transformers: insights from the social media datasets

Chapagain, S., Cascalheira, C. J., Hamdi, S. M., Boubrahimi, S. F., & Scheer, J. R. (2025) · Social Network Analysis and Mining · doi:10.1007/s13278-025-01521-z · Cited by 6 · see citing works

Low-Resource Similar Case Matching in Legal Domain

Fang, J., Li, X., & Liu, Y. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-15931-2_47 · Cited by 5 · see citing works

Steno AI at SemEval-2023 Task 6: Rhetorical Role Labelling of Legal Documents using Transformers and Graph Neural Networks

Gupta, A., Furniturewala, S., Kumari, V., & Sharma, Y. (2023) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/2023.semeval-1.256 · Cited by 7 · see citing works

Chinese Address Recognition Method Based on Multi-Feature Fusion

Wang, Y., Wang, M., Ding, C., Yang, X., & Chen, J. (2022) · IEEE Access · doi:10.1109/access.2022.3213976 · Cited by 5 · see citing works

TTG-Text: A Graph-Based Text Representation Framework Enhanced by Typical Testors for Improved Classification

Sánchez-Antonio, C., Valdez-Rodríguez, J. E., & Calvo, H. (2024) · Mathematics · doi:10.3390/math12223576 · Cited by 4 · see citing works

LOGIC: LLM-originated guidance for internal cognitive improvement of small language models in stance detection

Lee, W., Lee, J., & Kim, H. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2585 · Cited by 4 · see citing works

Research on Natural Language Misleading Content Detection Method Based on Attention Mechanism

Liu, B. (2025) · IEEE Access · doi:10.1109/access.2025.3591455 · Cited by 5 · see citing works

BHGAttN: A Feature-Enhanced Hierarchical Graph Attention Network for Sentiment Analysis

Zhang, J., Cui, Z., Park, H. J., & Noh, G. (2022) · Entropy · doi:10.3390/e24111691 · Cited by 4 · see citing works

Attention is Not Always What You Need: Towards Efficient Classification of Domain-Specific Text

Wahba, Y., Madhavji, N., & Steinbacher, J. (2023) · arXiv.org · doi:10.1007/978-3-031-37963-5_80 · Cited by 4 · see citing works

SEDGCN: Sentiment Enhanced Dual Graph Convolutional Networks for Detecting Adverse Drug Reactions

Qiu, Y., Zhang, X., Wang, W., Wu, Y., Xu, B., Liu, H., & Lin, H. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385261 · Cited by 4 · see citing works

Multi-document influence on readers: augmenting social emotion prediction by learning document interactions

Mou, X., Peng, Q., Sun, Z., Bashir, M. F., & Li, H. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-09420-8 · Cited by 4 · see citing works

Dialectic Feature-Based Fuzzy Graph Learning for Label Propagation Assisting Text Classification

Madhu, C., & Sudhakar, M. (2024) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2024.3421595 · Cited by 4 · see citing works

Adapting GNNs for Document Understanding: A Flexible Framework With Multiview Global Graphs

Wu, Z. X., Zhang, Q., Miao, D., Zhao, X., & Shi, K. (2024) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2024.3468890 · Cited by 4 · see citing works

DynGraph-BERT: Combining BERT and GNN Using Dynamic Graphs for Inductive Semi-Supervised Text Classification

Perin, E. L. S., de Souza, M. C., Silva, J. D. A., & Matsubara, E. T. (2025) · Informatics · doi:10.3390/informatics12010020 · Cited by 4 · see citing works

BN-GRAPH: Data Augmentation Based Bangla Text Sentiment Analysis in Deep Graph Neural Network

Bhowmik, N. R., Mondal, M. R. H., & Arifuzzaman, M. (2025) · SN Computer Science · doi:10.1007/s42979-025-03763-2 · Cited by 4 · see citing works

iAMP-EmGCN: A new design for identifying antimicrobial peptides based on BERT and Graph Convolutional Network

Xing, W., Zhang, J., Li, C., & Dong, G. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.127811 · Cited by 4 · see citing works

An Early Prediction and Label Smoothing Alignment Strategy for User Intent Classification of Medical Queries

Luo, Y., Huang, Z., Wong, L. P., Zhan, C., Wang, F. L., & Hao, T. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-6142-7_9 · Cited by 4 · see citing works

Research on Feature Fusion Method Based on Graph Convolutional Networks

Wang, D., & Chen, X. (2024) · Applied Sciences · doi:10.3390/app14135612 · Cited by 4 · see citing works

BertGCN: Transductive Text Classification by Combining GCN and BERTPreprint

Lin, Y., Meng, Y., Sun, X., Han, Q., Kuang, K., Li, J., & Wu, F. Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.05727 · Cited by 51 · see citing works

TextGCL: Graph Contrastive Learning for Transductive Text Classification

Zhao, Y., & Song, X. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191923 · Cited by 9 · see citing works

BERTGACN: Text Classification by Combining BERT and GCN and GAT

Yang, X. (2023) · International Conference on Neural Networks, Information and Communication Engineering (NNICE) · doi:10.1109/nnice58320.2023.10105710 · Cited by 3 · see citing works

A Joint Model for Text Classification with BERT-BiLSTM and GCN

Yuan, Y., Lv, S., Bao, Z., & Li, K. (2022) · doi:10.1145/3573942.3573970

VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification

Lu, Z., Du, P., & Nie, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-45439-5_25 · Cited by 157 · see citing works