Exploiting Generative AI to Scale up Intelligent Tutoring Systems

Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment

Li, Z., Li, H., Ralescu, A. L., Dillman, J. R., Altaye, M., Cecil, K. M., Parikh, N. A., & He, L. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102993 · Cited by 10

LIGHTHOUSE illuminates therapeutics for a variety of diseases including COVID-19

(2022) · doi:10.1016/j.isci.2022.105314 · Cited by 9

Not all layers are equally as important: Every Layer Counts BERT

Georges Gabriel Charpentier, L., & Samuel, D. (2023) · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning · doi:10.18653/v1/2023.conll-babylm.20 · Cited by 9

Detecting and Understanding Textual Deepfakes in Online Reviews

Kowalczyk, P., Röder, M., Dürr, A., & Thiesse, F. (2022) · Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.24251/hicss.2022.184 · Cited by 9

Revolutionizing optical networks: The integration and impact of large language models

Cruzes, S. (2025) · Optical Switching and Networking · doi:10.1016/j.osn.2025.100812 · Cited by 9

CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning

Wei, P., Yang, X., Liu, S., Wang, L., & Zheng, B. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track · doi:10.18653/v1/2022.naacl-industry.2 · Cited by 9

Bridging the gap: A survey of document retrieval techniques for high-resource and low-resource languages

Kazi, S., Khoja, S., & Daud, A. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100756 · Cited by 9

CAPE: a deep learning framework with Chaos-Attention net for Promoter Evolution

Ren, R., Yu, H., Teng, J., Mao, S., Bian, Z., Tao, Y., & Yau, S. S.-T. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae398 · Cited by 9

Pre-training with a rational approach for antibody sequence representation

Gao, X., Cao, C., He, C., & Lai, L. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1468599 · Cited by 9

Anomaly Detection in Spacecraft Telemetry Data Based on Transformer-LSTM

Jiang, S., Jiang, Y., Wang, Y., Zhang, X., & Zhang, Z. (2023) · 2023 International Conference on Intelligent Communication and Networking (ICN) · doi:10.1109/icn60549.2023.10426290 · Cited by 9

Clinical natural language processing for secondary uses

Gao, Y., Mahajan, D., Uzuner, Ö., & Yetisgen, M. (2024) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2024.104596 · Cited by 8

AI-Powered Game Design: Experts Employing ChatGPT in the Game Design Process

LANKES, M., & STOCKL, A. (2023) · The Eurasia Proceedings of Science Technology Engineering and Mathematics · doi:10.55549/epstem.1406194 · Cited by 8

Recommendations to Create Programming Exercises to Overcome ChatGPT

Berrezueta-Guzman, J., & Krusche, S. (2023) · doi:10.35542/osf.io/expuq · Cited by 27

Language-Models-as-a-Service: Overview of a New Paradigm and its Challenges

La Malfa, E., Petrov, A., Frieder, S., Weinhuber, C., Burnell, R., Nazar, R., Cohn, A., Shadbolt, N., & Wooldridge, M. (2024) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.15865 · Cited by 9

Multimodal Multi-Speaker Merger & Acquisition Financial Modeling: A New Task, Dataset, and Neural Baselines

Sawhney, R., Goyal, M., Goel, P., Mathur, P., & Shah, R. R. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · doi:10.18653/v1/2021.acl-long.526 · Cited by 8

A Multichannel Deep Learning Framework for Cyberbullying Detection on Social Media

Alotaibi, M., Alotaibi, B., & Razaque, A. (2021) · doi:10.20944/preprints202110.0070.v1 · Cited by 94

Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction

Zhang, W., Zhao, S., Meng, F., Wu, S., & Liu, M. (2023) · Proceedings of the 31st ACM International Conference on Multimedia · doi:10.1145/3581783.3612532 · Cited by 10

Learning Music Sequence Representation From Text Supervision

Chen, T., Xie, Y., Zhang, S., Huang, S., Zhou, H., & Li, J. (2022) · ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp43922.2022.9746131 · Cited by 8

SeaMoon: From protein language models to continuous structural heterogeneity

Lombard, V., Timsit, D., Grudinin, S., & Laine, E. (2025) · Structure · doi:10.1016/j.str.2025.06.010 · Cited by 8

The Cambridge Law Corpus: A Dataset for Legal AI Research

Östling, A., Sargeant, H., Xie, H., Bull, L., Terenin, A., Jonsson, L., Magnusson, M., & Steffek, F. (2024) · doi:10.2139/ssrn.4763429 · Cited by 8

3DRTE: 3D Rotation Embedding in Temporal Knowledge Graph

Wang, J., Zhang, W., Chen, X., Lei, J., & Lai, X. (2020) · IEEE Access · doi:10.1109/access.2020.3036897 · Cited by 8

Implementing Generative Artificial Intelligence in Precision Oncology: Safety, Governance, and Significance

Hamamoto, R., Koyama, T., Takahashi, S., Yasuda, T., Kobayashi, K., Akagi, Y., Kouno, N., Sudo, K., Hirata, M., Sunami, K., et al. (2026) · Journal of Hematology & Oncology · doi:10.1186/s13045-026-01781-y · Cited by 8

Main methods and tools for peptide development based on protein-protein interactions (PPIs)

Baeza, J., Bedoya, M., Cruz, P., Ojeda, P., Adasme-Carreño, F., Cerda, O., & González, W. (2025) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2025.151623 · Cited by 8

Multiagent Actor-Critic Generative AI for Query Resolution and Analysis

Ur Rahman, M. W., Nevarez, R., Mim, L. T., & Hariri, S. (2025) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2025.3544173 · Cited by 8

Designing optimal behavioral experiments using machine learning

Valentin, S., Kleinegesse, S., Bramley, N. R., Seriès, P., Gutmann, M. U., & Lucas, C. G. (2024) · eLife · doi:10.7554/elife.86224 · Cited by 8

Scoring alignments by embedding vector similarity

(2024) · doi:10.1093/bib/bbae178 · Cited by 8

Untitled work

(2022) · doi:10.18653/v1/2022.sigtyp-1.4 · Cited by 8

QSP ‐Copilot: An AI ‐Augmented Platform for Accelerating Quantitative Systems Pharmacology Model Development

Saini, A., & Farnoud, A. (2025) · CPT: Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.70127 · Cited by 7

Reflexivity in human-written and ChatGPT-generated English research article abstracts: A comparison of metadiscourse

Zhang, M., & Zhang, J. (2026) · Applied Linguistics · doi:10.1093/applin/amaf032 · Cited by 7

Insider Threat Detection Using Bidirectional Encoder Representations From Transformers and Optimized AdaBoost Classifier

Kumpf, K., Protic, M., Jovanovic, L., Cajic, M., Zivkovic, M., & Bacanin, N. (2024) · 2024 International Conference on Circuit, Systems and Communication (ICCSC) · doi:10.1109/iccsc62074.2024.10616526 · Cited by 7

Automatic analysis of available source code of top artificial intelligence conference papers

Lin, J., Wang, Y., Yu, Y., Zhou, Y., Chen, Y., & Shi, X. (2022) · International Journal of Software Engineering and Knowledge Engineering · doi:10.1142/s0218194022500358 · Cited by 7

The Early Bird Catches the Leak: Unveiling Timing Side Channels in LLM Serving Systems

Song, L., Pang, Z., Wang, W., Wang, Z., Wang, X., Chen, H., Song, W., Jin, Y., Meng, D., & Hou, R. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3622954 · Cited by 7

Is ChatGPT a friend or foe in the war on misinformation?: A South African perspective

Senekal, B., & Brokensha, S. (2023) · Communicare: Journal for Communication Studies in Africa · doi:10.36615/jcsa.v42i2.2437 · Cited by 7

AMEIR: Automatic Behavior Modeling, Interaction Exploration and MLP Investigation in the Recommender System

Zhao, P., Xiao, K., Zhang, Y., Bian, K., & Yan, W. (2021) · Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2021/290 · Cited by 7

Efficient inference, training, and fine-tuning of protein language models

Çelik, M. H., & Xie, X. (2025) · iScience · doi:10.1016/j.isci.2025.113495 · Cited by 7

PS4: A Next-Generation Dataset for Protein Single-Sequence Secondary Structure Prediction

Peracha, O. (2024) · BioTechniques · doi:10.2144/btn-2023-0024 · Cited by 7

SwinCell: a 3D transformer and flow-based framework for improved cell segmentation

Zhang, X., Lin, Z., Wang, L., Chu, Y. S., Yang, Y., Xiao, X., Lin, Y., & Liu, Q. (2025) · Communications Biology · doi:10.1038/s42003-025-08397-x · Cited by 7

Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets

Bejan, I., Sokolov, A., & Filippova, K. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2023.emnlp-main.625 · Cited by 7

Evaluating generative artificial intelligence adoption in management education using AI–human augmentation and expectation confirmation theory

Kumar, A., Baijal, A., & Kharat, M. (2025) · Journal of International Education in Business · doi:10.1108/jieb-07-2024-0086 · Cited by 6

Clinical Application of Large Language Models for Intervention Plan Development in Speech-Language Pathology

Kim, N., Homer, M., & Jang, H. (2025) · American Journal of Speech-Language Pathology · doi:10.1044/2025_ajslp-24-00464 · Cited by 9

Tailoring Your Code Companion: Leveraging LLMs and RAG to Develop a Chatbot to Support Students in a Programming Course

Alario-Hoyos, C., Kemcha, R., Kloos, C. D., Callejo, P., Estévez-Ayres, I., Santín-Cristóbal, D., Cruz-Argudo, F., & López-Sánchez, J. L. (2024) · 2024 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) · doi:10.1109/tale62452.2024.10834365 · Cited by 8

Integrating Protein-Protein Interaction Information into Drug Response Prediction by Graph Neural Encoding

Xie, Y., Peng, J., & Zhou, Y. (2019) · doi:10.21203/rs.2.18936/v1 · Cited by 5

Unraveling Online Mental Health Through the Lens of Early Maladaptive Schemas: AI-Enabled Content Analysis of Online Mental Health Communities

Ang, B. H., Gollapalli, S. D., Du, M., & Ng, S.-K. (2025) · Journal of Medical Internet Research · doi:10.2196/59524 · Cited by 6

Artificial intelligence: a challenge to scientific communication

Gauckler, C., & Werner, M. H. (2024) · Klinische Monatsblätter für Augenheilkunde · doi:10.1055/a-2418-5238 · Cited by 6

Exploring the Knowledge of an Outstanding Protein to Protein Interaction Transformer

Yang, S., Cheng, P., Liu, Y., Feng, D., & Wang, S. (2024) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2024.3381825 · Cited by 6

Improving AlphaFold Predicted Contacts for Alpha-Helical Transmembrane Proteins Using Structural Features

Sawhney, A., Li, J., & Liao, L. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25105247 · Cited by 6

Towards Generating Summaries for Lexically Confusing Code through Code Erosion

Yan, F., & Li, M. (2021) · Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2021/512 · Cited by 6

Missed Connections: Lateral Thinking Puzzles for Large Language Models

Todd, G., Merino, T., Earle, S., & Togelius, J. (2024) · 2024 IEEE Conference on Games (CoG) · doi:10.1109/cog60054.2024.10645557 · Cited by 6

Say What? Collaborative Pop Lyric Generation Using Multitask Transfer Learning

Ram, N., Gummadi, T., Bhethanabotla, R., Savery, R. J., & Weinberg, G. (2021) · Proceedings of the 9th International Conference on Human-Agent Interaction · doi:10.1145/3472307.3484175 · Cited by 6

An Exploratory Study of Argumentative Writing by Young Students: A transformer-based Approach

Ghosh, D., Beigman Klebanov, B., & Song, Y. (2020) · Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications · doi:10.18653/v1/2020.bea-1.14 · Cited by 6

Towards Explainable Recommendation Via Bert-Guided Explanation Generator

Zhan, H., Li, L., Li, S., Liu, W., Gupta, M., & Kot, A. C. (2023) · ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp49357.2023.10096389 · Cited by 6

Evaluating the Reliability of Vision Transformers for Space Robotics Applications

Bodmann, P. R., Rech, P., & Saveriano, M. (2024) · 2024 International Conference on Space Robotics (iSpaRo) · doi:10.1109/isparo60631.2024.10687576 · Cited by 5

No-reference image quality assessment based on global awareness

Hu, Z., Yang, G., Du, Z., Huang, X., Zhang, P., & Liu, D. (2024) · PLOS ONE · doi:10.1371/journal.pone.0310206 · Cited by 5

Trace Anomaly Detection for Microservice Systems via Graph-based Semi-supervised Learning

Ding, S., E, Y., Zhang, J., Li, L., Zhang, L., & Ge, J. (2024) · 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd61410.2024.10580078 · Cited by 5

Long-Term Memory for Large Language Models Through Topic-Based Vector Database

Zhang, Y., Yu, Z., Jiang, W., Shen, Y., & Li, J. (2023) · 2023 International Conference on Asian Language Processing (IALP) · doi:10.1109/ialp61005.2023.10337079 · Cited by 6

Fake it to make it: Using synthetic data to remedy the data shortage in joint multi-modal speech-and-gesture synthesis

Mehta, S., Deichler, A., O’Regan, J., Moëll, B., Beskow, J., Henter, G. E., & Alexanderson, S. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00201 · Cited by 7

An Unsupervised Method for Learning Representations of Multi-word Expressions for Semantic Classification

Vacareanu, R., Valenzuela-Escárcega, M. A., Sharp, R., & Surdeanu, M. (2020) · Proceedings of the 28th International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.297 · Cited by 5

SetQuence & SetOmic: Deep Set Transformer-based Representations of Cancer Multi-Omics

Jurenaite, N., León-Periñán, D., Donath, V., Torge, S., & Jäkel, R. (2022) · 2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · doi:10.1109/cibcb55180.2022.9863058 · Cited by 5

Exploring Sensor Impact and Architectural Robustness in Adverse Weather on BEV Perception

Kumar, S., Sharma, S., Asghar, R., Mohandas, R., Brophy, T., Sistu, G., Grua, E. M., Donzella, V., & Eising, C. (2025) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2025.3621862 · Cited by 5

Implicit Relation Linking for Question Answering over Knowledge Graph

Zhao, Y., Huang, J., Hu, W., Chen, Q., Qiu, X., Huo, C., & Ren, W. (2022) · Findings of the Association for Computational Linguistics: ACL 2022 · doi:10.18653/v1/2022.findings-acl.312 · Cited by 5

Mean BERTs make erratic language teachers: the effectiveness of latent bootstrapping in low-resource settings

Samuel, D. (2023) · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning · doi:10.18653/v1/2023.conll-babylm.19 · Cited by 5

Adapt-FuseNet: Context-aware multimodal adaptive fusion of face and gait features using attention techniques for human identification

Prakash, A., Thejaswin, S., Nambiar, A., & Bernardino, A. (2023) · 2023 IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb57857.2023.10448765 · Cited by 5

Large Language Models in Spine Surgery: A Promising Technology

Shah, R., & Schwab, J. H. (2025) · HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery · doi:10.1177/15563316251340696 · Cited by 5

Direct coupling analysis and the attention mechanism

(2025) · doi:10.1186/s12859-025-06062-y · Cited by 5

SAINT-Angle: self-attention augmented inception-inside-inception network and transfer learning improve protein backbone torsion angle prediction

Hasan, A. K. M. M., Ahmed, A. Y., Mahbub, S., Rahman, M. S., & Bayzid, M. S. (2023) · Bioinformatics Advances · doi:10.1093/bioadv/vbad042 · Cited by 5

Advanced deep learning architectures for accurate detection of subsurface tile drainage pipes from remote sensing images

Breitkopf, T.-L., Hackel, L., Ravanbakhsh, M., Cooke, A.-K., Willkommen, S., Broda, S., & Demir, B. (2022) · Image and Signal Processing for Remote Sensing XXVIII · doi:10.1117/12.2636263 · Cited by 5

MedRedQA for Medical Consumer Question Answering: Dataset, Tasks, and Neural Baselines

Nguyen, V., Karimi, S., Rybinski, M., & Xing, Z. (2023) · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2023.ijcnlp-main.42 · Cited by 5

Design and evaluation of a global workspace agent embodied in a realistic multimodal environment

Dossa, R. F. J., Arulkumaran, K., Juliani, A., Sasai, S., & Kanai, R. (2024) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2024.1352685 · Cited by 5

Intra-Template Entity Compatibility based Slot-Filling for Clinical Trial Information Extraction.

Witte, C., & Cimiano, P. (2022) · Proceedings of the 21st Workshop on Biomedical Language Processing · doi:10.18653/v1/2022.bionlp-1.18 · Cited by 5

Experience-guided multi-agent interpretable framework for radiology report summarization

Li, J., Zhou, T., Zhou, Z., Wei, X., Song, H., Wang, Z., Chen, Y., & Lv, H. (2026) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2025.109078 · Cited by 4

Dissecting Transformer Length Extrapolation via the Lens of Receptive Field Analysis

Chi, T.-C., Fan, T.-H., Rudnicky, A., & Ramadge, P. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2023.acl-long.756 · Cited by 5

LongCodeZip: Compress Long Context for Code Language Models

Shi, Y., Qian, Y., Zhang, H., Shen, B., & Gu, X. (2025) · 2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE) · doi:10.1109/ase63991.2025.00020 · Cited by 7

Representation and Extraction of Physics Knowledge Based on Knowledge Graph and Embedding-Combined Text Classification for Cooperative Learning

Shang, J., Huang, J., Zeng, S., Zhang, J., & Wang, H. (2022) · 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd54268.2022.9776230 · Cited by 4

Capturing the Long-Distance Dependency in the Control Flow Graph via Structural-Guided Attention for Bug Localization

Ma, Y.-F., Du, Y., & Li, M. (2023) · Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/249 · Cited by 4

Bridging the gap between structural and metabolic neuroimaging via MRI-to-PET synthesis: a tri-attention enhanced GAN approach

Sheng, J., Zhu, H., Zhou, R., Zhang, Q., Wang, J., & Ying, Z. (2025) · Brain Research · doi:10.1016/j.brainres.2025.149691 · Cited by 4

Unified Keyword Spotting and Audio Tagging on Mobile Devices with Transformers

Dinkel, H., Wang, Y., Yan, Z., Zhang, J., & Wang, Y. (2023) · ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp49357.2023.10095534 · Cited by 4

Characterizing verbatim short-term memory in neural language models

Armeni, K., Honey, C., & Linzen, T. (2022) · Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL) · doi:10.18653/v1/2022.conll-1.28 · Cited by 4

Context Is King: Large Language Models’ Interpretability in Divergent Knowledge Scenarios

Piñeiro-Martín, A., Santos-Criado, F.-J., García-Mateo, C., Docío-Fernández, L., & López-Pérez, M. D. C. (2025) · Applied Sciences · doi:10.3390/app15031192 · Cited by 4

Guiding a language-model based protein design method towards MHC Class-I immune-visibility targets in vaccines and therapeutics

(2024) · doi:10.1016/j.immuno.2024.100035 · Cited by 4

Protein language model identifies disordered, conserved motifs implicated in phase separation

Zhang, Y., Zheng, J., & Zhang, B. (2025) · eLife · doi:10.7554/elife.105309 · Cited by 4

Blind Face Restoration under Extreme Conditions: Leveraging 3D-2D Prior Fusion for Superior Structural and Texture Recovery

Chen, Z., Lu, L., Yuan, Z., Zhu, Y., Li, Y., Yuan, C., & Deng, W. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i2.27889 · Cited by 3

Distant-cto: a zero cost, distantly supervised approach to improve low-resource entity extraction using clinical trials literature.

Dhrangadhariya, A., & Müller, H. (2022) · Proceedings of the 21st Workshop on Biomedical Language Processing · doi:10.18653/v1/2022.bionlp-1.34 · Cited by 3

Cost-sensitive PLM-based Approach for Arabic and English Cyberbullying Classification

Harbaoui, A., Benaissa, A. R., & ghezala, H. B. (2023) · doi:10.21203/rs.3.rs-2524732/v1 · Cited by 3

A Neural Network Architecture for Children’s Audio–Visual Emotion Recognition

(2023) · doi:10.3390/math11224573 · Cited by 3

Multimodal graph, surface, and language-based model for protein protein interaction prediction

Arteaga, D., Chervov, N., & Poptsova, M. (2026) · Scientific Reports · doi:10.1038/s41598-025-34758-x · Cited by 3

Self-Attention Based Vision Processing for Prosthetic Vision

White, J., Ruiz-Serra, J., Petrie, S., Kameneva, T., & McCarthy, C. (2023) · 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) · doi:10.1109/embc40787.2023.10341053 · Cited by 3

Incorporating subjectivity into gendered ambiguous pronoun (GAP) resolution using style transfer

Pant, K., & Dadu, T. (2022) · Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing (GeBNLP) · doi:10.18653/v1/2022.gebnlp-1.28 · Cited by 3

A Slice and Dice Approach to Accelerate Compound Sparse Attention on GPU

Li, H., Choi, J., & Ahn, J. H. (2022) · 2022 IEEE International Symposium on Workload Characterization (IISWC) · doi:10.1109/iiswc55918.2022.00019 · Cited by 3

ExDDV: A New Dataset for Explainable Deepfake Detection in Video

Hondru, V., Hogea, E., Onchiş, D., & Ionescu, R. T. (2026) · 2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv61042.2026.00416 · Cited by 3

Structural-temporal coupling anomaly detection with dynamic graph transformer

Zong, C., Zhuang, Y., Shao, J., & Lu, W. (2026) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-025-01176-6 · Cited by 3

Joint extraction of entity and relation based on fine-tuning BERT for long biomedical literatures

Gao, T., Zhai, X., Yang, C., Lv, L., & Wang, H. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbae194 · Cited by 2

Work-in-Progress: Course-based Undergraduate Research Experience (CURE) with Generative AI in a Computer Science Course

Lauren, P. (2024) · 2024 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893139 · Cited by 2

DilatedFormer: dilated granularity transformer network for placental maturity grading in ultrasound

Wu, Y., Yang, Y., Zhu, L., Han, Z., Luo, H., Xue, X., & Wang, W. (2023) · Frontiers in Physics · doi:10.3389/fphy.2023.1239400 · Cited by 2

Visual Prostheses in the Era of Artificial Intelligence Technology

Sarbout, I., Gungor, A., Ounissi, M., Zaher, S., Ptito, M., Kupers, R., Racoceanu, D., & Milea, D. (2025) · Eye and Brain · doi:10.2147/eb.s524322 · Cited by 3

IDMatchHAR: Semi-Supervised Learning for Sensor-Based Human Activity Recognition Using Pretraining

Takenaka, K., Sakai, S., & Hasegawa, T. (2025) · IEEE Sensors Letters · doi:10.1109/lsens.2025.3546985 · Cited by 3

Next-Day Medical Activities Recommendation Model with Double Attention Mechanism Using Generative Adversarial Network

Li, W., Yang, J., & Min, X. (2022) · Journal of Healthcare Engineering · doi:10.1155/2022/6334435 · Cited by 2

Emotion Classification With Visibility Graphs

Şimşek, E., Topcu, A., Koç, E., Saritas, E. U., & Koç, A. (2025) · IEEE Signal Processing Letters · doi:10.1109/lsp.2025.3567033 · Cited by 2

Fusion or defusion? Flexible vision-and-language pre-training

Sun, R., Li, Z., Ding, Y., Wang, Q., Wang, J., Zheng, H., Wu, W., & Xian, Y. (2023) · Findings of the Association for Computational Linguistics: ACL 2023 · doi:10.18653/v1/2023.findings-acl.316 · Cited by 2

Decider: A Dual-System Rule-Controllable Decoding Framework for Language Generation

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