Publications and Patents

95 entries — 94 peer-reviewed papers and 1 granted patent, most recent first

95 of 95

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20267 papers and 1 patent
  1. Dao Viet Hang, Dao Van Long, Nguyen Thi Thuy, Dinh Viet Sang, Vu Hai, Tran Thi Thanh Hai, Vu Thi Ly. Multi-task method for automatic detection and classification of lesions from upper gastrointestinal endoscopy video streams. Invention Patent No. 58155, granted 11 May 2026 (Application 1-2024-05180, filed 12 July 2024) · Proprietor: Institute of Gastroenterology and Hepatology. Patent
  2. NQN Minh, NH Dang, N Van Linh, Dinh Viet Sang, DA Nguyen. AQS-IDETR: Adaptive Query Selection for Efficient Inference in Real-Time Detection Transformers. Image and Vision Computing, Vol. 173, 106097, 2026. ISI Q1
  3. NL Hai, LN Van, Dinh Viet Sang. Mozila: Continual Event Detection Through the Lens of Multi-Objective Optimization and Language Model Head Preservation. Computational Linguistics, 2026. ISI Q1
  4. MC Xuan, TP Nguyen, LN Van, Dinh Viet Sang, NTN Diep, T Le. LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026). CORE A*
  5. TV Nguyen, N Van Dong, MC Xuan, T Nguyen, LN Van, Dinh Viet Sang, T Le. Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models. Findings of the Association for Computational Linguistics: EACL 2026, 3609-3629. CORE A
  6. DT Vu, PK Chi, DP Van, LN Van, Dinh Viet Sang, T Le. DWA-KD: Dual-Space Weighting and Time-Warped Alignment for Cross-Tokenizer Knowledge Distillation. Findings of the Association for Computational Linguistics: EACL 2026, 3513-3527. CORE A
  7. MN Ta, DC Van, DA Hoang, M Le-Anh, T Nguyen, MAT Nguyen, Y Wang, …, Dinh Viet Sang. FAID: Fine-grained AI-generated Text Detection using Multi-task Auxiliary and Multi-level Contrastive Learning. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026). CORE A
  8. T Nguyen, LN Van, AN Duc, Dinh Viet Sang. Global and Local Context in Short Text Neural Topic Model. Artificial Intelligence, 104502, 2026. ISI Q1
202516 papers
  1. CP Khanh, HT Vuong, Dinh Viet Sang, LN Van. A Framework for Neural Topic Modeling using Hierarchical Clustering and Contrastive Learning with Optimal Transport. Neurocomputing, 132530, 2025. ISI Q1
  2. NH Lam, VD Minh, NT Tuan, NQ Tri, NVN Khue, Dinh Viet Sang. ZenID: FaceFusionNet-Guided Diffusion for Parent-to-Child Facial Prediction. 2025 17th International Conference on Knowledge and Systems Engineering (KSE 2025).
  3. NH Lam, NT Tuan, VD Minh, NVN Khue, NQ Tri, Dinh Viet Sang. Sketch2Comic: A Diffusion-Based Framework for Consistent Multi-Character Comic Synthesis. 2025 17th International Conference on Knowledge and Systems Engineering (KSE 2025).
  4. T Le, HT Vuong, T Nguyen, LN Van, Dinh Viet Sang, T Le, TH Nguyen. Multi-Surrogate-Objective Optimization for Neural Topic Models. Findings of the Association for Computational Linguistics: EMNLP 2025, 135-151. CORE A*
  5. VH Duong, H Vu, HD Phan, DQ Nguyen, DH Pham, QT Le, BS Nguyen, …, Dinh Viet Sang. ThyroidXL: Advancing Thyroid Nodule Diagnosis with an Expert-Labeled, Pathology-Validated Dataset. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2025). CORE A
  6. T Nguyen, LN Van, AN Duc, Dinh Viet Sang. A Framework for Neural Topic Modeling with Mutual Information and Group Regularization. Neurocomputing, Vol. 645, 130420, 2025. ISI Q1
  7. T Nguyen, DT Pham, QD Nguyen, LN Van, AN Duc, Dinh Viet Sang. TopicOT: Neural Topic Model Aligning with Pre-trained Clustering and Optimal Transport. Neurocomputing, 131268, 2025. ISI Q1
  8. HT Vuong, T Le, T Vu, T Nguyen, LN Van, Dinh Viet Sang, TH Nguyen. HiCOT: Improving Neural Topic Models via Optimal Transport and Contrastive Learning. Findings of the Association for Computational Linguistics: ACL 2025, 13894-13920. CORE A*
  9. T Vu, M Do, T Nguyen, LN Van, Dinh Viet Sang, TH Nguyen. Topic Modeling for Short Texts via Optimal Transport-based Clustering. Findings of the Association for Computational Linguistics: ACL 2025, 7666-7680. CORE A*
  10. TD Pham, N Le Hai, LN Van, NTN Diep, Dinh Viet Sang, TH Nguyen. Mitigating Non-representative Prototypes and Representation Bias in Few-shot Continual Relation Extraction. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025). CORE A*
  11. H Le, N Luu, T Nguyen, T Dao, Dinh Viet Sang. Optimizing Answer Generator in Vietnamese Legal Question Answering Systems using Language Models. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 2025. ISI Q2
  12. T Nguyen, T Le, HT Vuong, QD Nguyen, DA Nguyen, LN Van, Dinh Viet Sang, et al. Sharpness-aware Minimization for Topic Models with High-quality Document Representations. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025). CORE A
  13. TN Nguyen, N Le Hai, ND Hieu, DA Nguyen, LN Van, TH Nguyen, …, Dinh Viet Sang. Improving Vietnamese-English Cross-Lingual Retrieval for Legal and General Domains. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025). CORE A
  14. AD Le, N Le Hai, TX Nguyen, LN Van, NTN Diep, Dinh Viet Sang, TH Nguyen. Enhancing Discriminative Representation in Similar Relation Clusters for Few-shot Continual Relation Extraction. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025). CORE A
  15. QD Nguyen, T Nguyen, DA Nguyen, LN Van, Dinh Viet Sang, TH Nguyen. GloCOM: A Short Text Neural Topic Model via Global Clustering Context. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025). CORE A
  16. L Tran, T Vo, A Nguyen, Dinh Viet Sang, V Nguyen. More Reliable Pseudo-labels, Better Performance: A Generalized Approach to Single Positive Multi-label Learning. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2025). CORE A*
20243 papers
  1. NM Chau, Dinh Viet Sang. A Diffusion Model for Personalized Text-to-Image Generation. International Symposium on Information and Communication Technology (SoICT 2024), 418-431.
  2. Z Ren, Dinh Viet Sang, PM Wong, CB Chng, JJY Too, TW Foong, WNH Loh, et al. G2LCPS: End-to-end Semi-supervised Landmark Prediction with Global-to-local Cross Pseudo Supervision for Airway Difficulty Assessment. Computers in Biology and Medicine, Vol. 183, 109246, 2024. ISI Q1
  3. MC Nguyen, TG Le, Dinh Viet Sang. HyperPolypDEQ: A Lightning Transformer-Based Deep Equilibrium Model for Colon Polyp Segmentation. Journal of Science and Technology: Smart Systems and Devices, Vol. 34 (3), 17-26, 2024.
202310 papers
  1. Nguyen Minh Chau, Nguyen Ngoc Toan, Le Dinh Tuyen, Dinh Viet Sang, Pooi-Mun Wong, Chin-Boon Chng and Chee-Kong Chui. Boosting Facial Landmark Detection via Self-supervised and Semi-supervised Learning. SoICT 2023
  2. Vu Quoc Hung, Tran Le Phuong Thao, Trinh Xuan Minh, Dinh Viet Sang. LSegDiff: A Latent Diffusion Model for Medical Image Segmentation. SoICT 2023
  3. Nguyen Quang Duc, Tran Khanh Luong, Le Hong Duc, Nguyen Huy Hoan, Trinh Anh Phuc, Dinh Viet Sang. Improving Single Positive Multi-label Classification via Knowledge-based Label-weighted Large Loss Rejection. SoICT 2023
  4. Duong Kien, Nguyen Thi Oanh, Dinh Viet Sang. MCLDA: Multi-level Contrastive Learning for Domain Adaptive Semantic Segmentation. SoICT 2023
  5. Ren-Jun Soon, Dinh Viet Sang, Chin-Boon Chng, Chee-Kong Chui. Explainable AI for CPS-Based Manufacturing Workcell. ICSSE 2023: 332-337
  6. Pham Van Toan, Dinh Viet Sang. M3C-Polyp — Mixed Momentum Model Committee for Improved Semi-Supervised Learning in Polyp Segmentation. BDCI 2023
  7. Nguyen Van Giang, Nguyen Minh Son, Kieu Anh Van, Tran Cat Khanh, Pham Ngoc Minh, Dinh Viet Sang. One-stage Robotic Grasp Detection. KSE 2023
  8. Nguyen Hong Son, Nguyen Thanh Huyen, Dinh Viet Sang. Semi-Supervised Learning with Dense Target Producer for End-to-end Lightweight Polyp Detection. KSE 2023
  9. Nguyen Viet Hoai, Pham Vu Hung, Dinh Viet Sang. Memory-Driven Region Contrast for Enhanced Polyp Semantic Segmentation. MAPR 2023 Best Paper Award
  10. Pham Van Toan, Dinh Viet Sang. ESSL-Polyp — A Robust Framework of Ensemble Semi-Supervised Learning in Polyp Segmentation. Computing Conference 2023
202211 papers
  1. Dinh Viet Sang, Do Duy Quang. Incremental Boundary Refinement using Self Axial Reverse Attention and Uncertainty-aware Gate for Colon Polyp Segmentation. SoICT 2022
  2. Nam Kieu Dang, Oanh Nguyen Thi, Thuy Nguyen Thi, Hang Dao Viet, Long Dao Van, Trung Tran Quang, Dinh Viet Sang. A Coarse-to-fine Unsupervised Domain Adaptation Method for Cross-Mode Polyp Segmentation. KSE 2022
  3. Manh Nguyen Duy, Hang Dao Viet, Long Dao Van, Hung Le Quang, Khanh Pham Cong, Oanh Nguyen Thi, Thuy Nguyen Thi, Dinh Viet Sang. EndoUNet: A Unified Model for Anatomical Site Classification, Lesion Categorization and Segmentation for Upper Gastrointestinal Endoscopy. KSE 2022 Best Paper Award
  4. Toan Pham Van, Linh Doan Bao, Duc Tran Trung and Quan Nguyen Van, Dinh Viet Sang. Online pseudo labeling for polyp segmentation with momentum networks. KSE 2022
  5. Kieu Dang Nam, Nguyen Minh Tu, Trinh Van Dieu, Muriel Visani, Nguyen Thi Oanh, Dinh Viet Sang. A Novel Unsupervised Domain Adaption Method for Depth-guided Semantic Segmentation using Coarse-to-fine Alignment. IEEE Access 2022 ISI Q1
  6. Nguyen Minh Chau, Le Truong Giang, Dinh Viet Sang. PolypDEQ: Towards Effective Transformer-based Deep Equilibrium Models for Colon Polyp Segmentation. ISVC 2022
  7. Nguyen Tuan Hung, Phan Ngoc Lan, Nguyen Thi Oanh, Nguyen Thi Thuy, Dinh Viet Sang. GCEENet: A Global Context Enhancement and Exploitation for Medical Image Segmentation. ISVC 2022
  8. Nguyen Thanh Duc, Nguyen Thi Oanh, Nguyen Thi Thuy, Tran Minh Triet, Dinh Viet Sang. ColonFormer: An Efficient Transformer Based Method for Colon Polyp Segmentation. IEEE Access, vol. 10, pp. 80575-80586, 2022 ISI Q1
  9. Toan Pham Van, Dinh Viet Sang, Linh Bao Doan, Thanh Tung Nguyen, Quang Hung Nguyen, Duc Trung Tran. Improve polyp semi-supervised segmentation with prioritizing the reliability of unlabeled images. ICSIE, 2022.
  10. Nguyen Viet Manh, Kieu Dang Nam, Dinh Viet Sang, Thi-Oanh Nguyen. G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation. Proceedings of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), 2022.
  11. Nguyen Sy An, Phan Ngoc Lan, Dao Viet Hang, Dao Van Long, Tran Quang Trung, Nguyen Thi Thuy, Dinh Viet Sang. BlazeNeo: Blazing fast polyp segmentation and neoplasm detection. IEEE Access, Vol. 10, 2022, pp. 43669-43684 ISI Q1
20215 papers
  1. Nguyen Viet Hoai, Phan Huy Hoang, Doan Bao Linh, Dinh Viet Sang. An End-to-End Spatial-Aware Attention Method for Multi-Line License Plate Spotting. The 5th International Conference on Future Networks & Distributed Systems (ICFNDS 2021)
  2. Dinh Viet Sang, Lam Xuan Thu. FastTacotron: A Fast, Robust and Controllable Method for Speech Synthesis. Proceedings of the MAPR (2021)
  3. Lan, P.N., An, N.S., Hang, D.V., Long, D.V., Trung, T.Q., Thuy, N.T., Dinh Viet Sang. NeoUnet: Towards accurate colon polyp segmentation and neoplasm detection. Proceedings of the 16th International Symposium on Visual Computing (2021)
  4. Nguyen Trong Thai, Nguyen Hoang Thuan, Dinh Viet Sang. An Improved Deep Neural Network Based on a Novel Visual Attention Mechanism for Text Recognition. RIVF 2021
  5. Nguyen Ba Hung, Nguyen Thanh Duc, Thai Van Chien, Dinh Viet Sang. AG-ResUNet++: An improved encoder-decoder based method for polyp segmentation in colonoscopy images. RIVF 2021
20207 papers
  1. In Seop Na, Chung Tran, Dung Nguyen, Dinh Viet Sang. Facial UV Map Completion for Pose-invariant Face Recognition: A Novel Adversarial Approach based on Coupled Attention Residual UNets. Human-centric Computing and Information Sciences 2020. ISI Q1
  2. Dinh Viet Sang, Nguyen Hoang Thuan. An EfficientNet-Like Feature Extractor and Focal CTC Loss for Image-Base Sequence Recognition. NICS 2020.
  3. Tran Phuong Nam, Dinh Viet Sang. A Pose Estimation Method for Multiple Identity Cards Based on Corner Heatmaps and Part Affinity Fields. NICS 2020.
  4. Nguyen Thanh Hau, Le Cong Hau, Dinh Viet Sang, Tingting Yao, Wei Li, Zhiyong Wang. Efficient Brain Tumor Segmentation with Dilated Multi-fiber Network and Weighted Bi-directional Feature Pyramid Network. DICTA 2020.
  5. Tran Thi Thanh Hai, Nguyen Tien Hai, Dinh Viet Sang. Significant Trajectories and Locality Constrained Linear Coding for Hand Gesture Representation. IEEE ICCE 2020.
  6. Nguyen Thanh Dat, Nguyen Dang Tuan Anh, Dinh Viet Sang. PCA-based 3D Facial Reenactment From Single Image. MAPR 2020.
  7. Tran Quang Chung, Hoang Cao Huyen, Dinh Viet Sang. A Novel Generative Model to Synthesize Face Images for Pose-invariant Face Recognition. MAPR 2020.
20195 papers
  1. Dinh Viet Sang, Le Tran Bao Cuong. Improving CRNN with EfficientNet-like feature extractor and multi-head attention for text recognition. SoICT 2019, pp 285-290
  2. Dinh Viet Sang, Duong Viet Hung. YOLOv3-VD: A sparse network for vehicle detection using variational dropout. SoICT 2019, pp 280-284
  3. Dinh Viet Sang, Phan Ngoc Lan. BK.Synapse: A scalable distributed training framework for deep learning. SoICT 2019, pp. 43-48.
  4. Huong-Giang Doan, Thanh-Hai Tran, Hai Vu, Thi-Lan Le, Van-Toi Nguyen, Dinh Viet Sang, Thi-Oanh Nguyen, Thi-Thuy Nguyen, Duy-Cuong Nguyen. Multi-view discriminant analysis for dynamic hand gesture recognition. The 5th Asian Conference on Pattern Recognition ACPR 2019
  5. Pham Cong Thang, Tran Thi Thu Thao, Phan Tran Dang Khoa, Dinh Viet Sang, Pham Minh Tuan, Nguyen Minh Hieu. An adaptive algorithm for restoring image corrupted by mixed noise. Cybernetics and physics, Vol. 8, No. 2. 2019, 73-82 (ISI).
20185 papers
  1. Dinh Viet Sang, Nguyen Duc Minh. Fully Residual Convolutional Neural Networks for Aerial Image Segmentation. SoICT 2018, pp 289-296
  2. Dinh Viet Sang, Hoang Trung Dung. Two-stream Deep Residual Learning with Fisher Criterion for Human Action Recognition. SoICT 2018, pp 297-304
  3. Dinh Viet Sang, Dang Manh Cuong and Le Tran Bao Cuong. An Effective Ensemble Deep Learning Framework for Malware Detection. SoICT 2018, pp 192-199
  4. Dinh Viet Sang, Le Tran Bao Cuong. Effective Deep Multi-source Multi-task Learning Frameworks for Smile Detection, Emotion Recognition and Gender Classification. Informatica, Vol. 42, No. 3, 2018, pp 345-356 (SCOPUS, ESCI)
  5. Dinh Viet Sang, Le Tran Bao Cuong, Pham Thai Ha. Discriminative Deep Feature Learning for Facial Emotion Recognition. MAPR 2018, pp. 1-6
20176 papers
  1. Trinh Anh Phuc, Dinh Viet Sang. Heuristic algorithm for extracting a subset of maximal cliques inside graphs. Journal of Science & Technology 123 (2017) 054-058.
  2. Dinh Viet Sang, Le Tran Bao Cuong, Vu Van Thieu. Multi-task learning for smile detection, emotion recognition and gender classification. SoICT 2017, pp. 340-347
  3. Thuy Nguyen Thi, Dinh Viet Sang, Quang Nguyen Tien and Thi Thanh Binh Huynh. Semantic Segmentation of Objects from Airborne Imagery. The Fourth Asia Conference on Defense Technology, Japan (ACDT 2017), pp. 1-6
  4. Xuan Cuong Pham, Manh Truong Dang, Dinh Viet Sang, Son Hoang, Tien Thanh Nguyen, Alan Wee-Chung Liew. Learning from Data Stream Based on Random Projection and Hoeffding Tree Classifier. DICTA 2017, pp. 1-8
  5. Dinh Viet Sang, Le Tran Bao Cuong, Do Phan Thuan. Facial Smile Detection Using Convolutional Neural Networks. KSE 2017, pp. 136-141
  6. Dinh Viet Sang, Nguyen Van Dat, Do Phan Thuan. Facial Recognition Using Deep Convolutional Neural Networks. KSE 2017, pp. 130-135
20164 papers
  1. Dao Duy Son, Dinh Viet Sang, Huynh Thi Thanh Binh, Nguyen Thi Thuy. Label associated dictionary pair learning for face recognition. SoICT 2016, pp. 302-307
  2. Dang N. H. Thanh, Dinh Viet Sang, Dvoenko Sergey. Colour image denoising based on a combined model. SoICT 2016, pp. 308-315
  3. Thanh N. H. Dang, Dvoenko Sergey D., Dinh Viet Sang. A Mixed Noise Removal Method Based on Total Variation. Informatica 2016, pp. 159-167 (SCOPUS, ESCI)
  4. Nguyen Thi Thuy, Dinh Viet Sang, Huynh Thi Thanh Binh. A New Approach for Learning Discriminative Dictionary for Pattern Classification. Journal of Information Science and Engineering, Vol. 32 No. 4, pp. 1113-1127 (July 2016) (SCI-E Index)
20154 papers
  1. Thanh N. H. Dang, Dvoenko Sergey D., Dinh Viet Sang. A Denoising Method Based on Total Variation. SoICT 2015: 223-230
  2. Nguyen Tien Quang, Nguyen Thi Thuy, Dinh Viet Sang, Huynh Thi Thanh Binh. An Efficient Framework for Pixel-wise Building Segmentation from Aerial Images. SoICT 2015: 282-287
  3. Nguyen Duc Tuan, Nguyen Quang Manh, Dinh Viet Sang, Huynh Thi Thanh Binh, Nguyen Thi Thuy. A Study on Non-sparse Dictionary Learning for Pattern Classification. KSE 2015: 371-376
  4. Nguyen Quang Manh, Nguyen Duc Tuan, Dinh Viet Sang, Huynh Thi Thanh Binh, Nguyen Thi Thuy. Uniform Detection in Social Image Streams. KSE 2015: 180-185
20143 papers
  1. Dvoenko S.D., Dinh Viet Sang. Evaluation of parametric acyclic Markov models for dependent objects. Machine Learning and Data Analysis. 2014. V. 1, No. 8, pp. 1068-1076.
  2. Dinh Viet Sang, Mai Dinh Loi, Nguyen Tien Quang, Huynh Thi Thanh Binh, Nguyen Thi Thuy. Improving semantic texton forests with a Markov random field for image segmentation. Proc. SoICT 2014, pp. 162-170.
  3. Dinh Viet Sang. Algorithms for selecting parameters of combination of acyclic adjacency graphs in the problem of texture image processing. Electronic Letters on Computer Vision and Image Analysis 13(2):35-37, 2014.
20132 papers
  1. Dvoenko S., Dinh Viet Sang. Cross-Validation of Parametric Acyclic Models of Interrelated Objects. Proc. XI International Conference «Pattern Recognition and Image Analysis». 2013, Vol. 1, pp. 177-181.
  2. Dvoenko S.D., Dinh Viet Sang. Estimating Parameters of Acyclic Markov Models in Raster Texture Image Segmentation (in Russian). Izvestiya TSU. Technical Sciences. 2013, Vol. 2, pp. 86-95.
20124 papers
  1. Dvoenko S.D., Dinh Viet Sang. Raster Texture Image Recognition based on Parametric Acyclic Markov Fields (in Russian). Proc. XXII International conference in Computer Graphic and Vision «GraphiCon-2012». Moscow: Maks Press, 2012, pp. 139-143.
  2. Dvoenko S.D., Dinh Viet Sang. Parametric Acyclic Markov Models in the problem of Interrelated Object Recognition (in Russian). Proc. IX International Conference «Intellectualization of Information Processing». Moscow: Torus Press, 2012, pp. 18-21.
  3. Dvoenko S.D., Dinh Viet Sang. Algorithms for Adjusting Parameters of Combination of Acyclic Adjacency Graphs in the Problem of Texture Image Recognition (in Russian). Izvestiya TSU. Technical Sciences. 2012, Vol. 3, pp. 253-262.
  4. Dvoenko S.D., Dinh Viet Sang. Algorithms for Adjusting Parameters of a Tree-like Markov Random Field in the Problem of Raster Texture Image Recognition (in Russian). Izvestiya TSU. Natural Sciences. 2012, Vol. 1, pp. 98-109.
20101 paper
  1. Dvoenko S.D., Savenkov D.S., Dinh Viet Sang. Acyclic Markov Models in Analysis of Interrelated Data Array (in Russian). Izvestiya TSU. Natural Sciences. 2010, Vol. 2, pp. 173-185.
20091 paper
  1. Dvoenko S.D., Savenkov D.S., Dinh Viet Sang. Combination of Acyclic Adjacency Graphs in the Problem of Markov Random Field Recognition (in Russian). Proc. XIV conference «Mathematical methods for Pattern Recognition». Moscow: Maks Press, 2009, pp. 441-444.

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