Explainable AI (XAI): Core Ideas, Techniques, and Solutions

Dwivedi, Rudresh, Dave, Devam, Naik, Het, Singhal, Smiti, Omer, Rana, Patel, Pankesh, Qian, Bin, Wen, Zhenyu +3 more·2023·ACM Computing Surveys

Cited by (1,002)

Items 501–600 of 1,002

  1. Building Human-AI Reliance Through Cognitive Engagement and Exploratory AI Assistance
    Muhammad Raees, Vassilis-Javed Khan, Konstantinos Papangelis · 2025 · ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
  2. Green Policies for a Sustainable Future: Best Practices in Transparent Monitoring and Adaptive Strategies in Management Disciplines
    Prerna Srivastava, Udit Mamodiya, Vineet Pandey, P. K. Dutta · 2026 · Springer eBooks
  3. Explainable AI–Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study
    Francis Ngema, Albert Whata, Micheal Olusoji Olusanya, Siyabonga Mhlongo · 2025 · JMIR AI
  4. A Holistic Review of Fuzzing for Vulnerability Assessment in Industrial Network Protocols
    Ahmed Mohamed Reda, Nour Moustafa, Erandi Lakshika · 2025 · IEEE Open Journal of the Communications Society
  5. Enhancing financial decision-making under cyber threats: a dual-branch framework integrating bayesian deep learning and explainable AI
    Yuhe Wu, Yuran Chen, Zhuang Liu · 2025 · Annals of Operations Research
  6. Communicating complex statistical models to a public health audience: translating science into action with the FARSI approach
    Mattia Stival, Lorenzo Schiavon, Gaia Bertarelli · 2025 · Research Square
  7. Visual Sampling Behavior Does not Explain Risk Perception: A Data-Driven xAI Investigation
    Martin Lorenz, Jan Hilbert, Philipp Michael Markus Peter Asteriou, Philipp Wintersberger, Patrick Ebel · 2025 · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI)
  8. Visualizing with Explainable AI Methods to Predict Injury Severity in Traffic Incidents
    Ovidiu Jianu, Monica Drăgoicea, Fadi Hosni · 2024 · International Conference on System Theory, Control and Computing (ICSTCC)
  9. Ethical Artificial Intelligence and Machine Learning in Self-Service Technologies
    Reshmi Ghosh, Eriona Çela, Souymodip Chakraborty, Bijoy Gupta, Gourab Dutta, Sanjukta Chakraborty, Surath Roy · 2025 · IGI Global eBooks
  10. Analyzing Hate Speech Detection using Explainable AI
    Ashish Parasar, Vandana Sharma, Preety Shoran · 2024 · IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)
  11. A Review of Explainable AI for Android Malware Detection and Analysis
    Maryam Tanha, Somayeh Kafaie · 2025 · IEEE Access
  12. Quantitative fairness—A framework for the design of equitable cybernetic societies
    Kevin Riehl, Anastasios Kouvelas, Michail Makridis · 2025 · Computers in Human Behavior Artificial Humans
  13. Optimizing Dementia Diagnosis Through Distance-Correlation Feature Space and Dimensionality Reduction
    Pablo Zubasti, Miguel Angel Patricio, Antonio Berlanga · 2025 · International Journal of Neural Systems
  14. VIME: Visual Interactive Model Explorer for Identifying Capabilities and Limitations of Machine Learning Models for Sequential Decision-Making
    Anindya Das Antar, Somayeh Molaei, Yan-Ying Chen, Matthew L. Lee, Nikola Banovic · 2024 · ACM Symposium on User Interface Software and Technology
  15. Knowledge-Enriched Graph Convolution Network for Hybrid Explainable Recommendation from Review Texts and Reasoning Path
    Rama Bastola, Subarna Shakya · 2024 · International Conference on Inventive Computation Technologies (ICICT)
  16. State-of-Health Estimation for Li-Ion Batteries of Real-World Electric Vehicles: Progress, Challenges, and Prospects
    Ren Zhu, Hamza Shaukat, Fatima Zahira, Hafiz Muhammad Huzefa, Muaaz Bin Kaleem, Hui Li · 2026 · Batteries
  17. Fine-Tuning Protein Language Models Unlocks the Potential of Underrepresented Viral Proteomes
    Sawhney, Rajan, Ferrell, Barbra, Dejean, Thibaut, Schreiber, Zachary, Harrigan, William, Polson, Shawn W., Wommack, K. Eric, Belcaid, Mahdi · 2025
  18. Few-shot learning and explainable AI for colon cancer histopathology: A prototypical network with multi-technique interpretability
    Asma Merabet, Asma Saighi, Zakaria Laboudi, Mohamed Abderraouf Ferradji, Saad Harous, Ali Wagdy Mohamed, Seyed Jalaleddin Mousavirad, Abdulaziz S. Almazyad · 2025 · International Journal of Medical Informatics
  19. A Next Generation Architecture for Internet of Things in the Automotive Supply Chain for Electric Vehicles
    Panagiotis Kapsalis, Giovanni Rimassa, Engin Zeydan · 2024 · ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc)
  20. An Explainable Artificial Intelligence Based Approach for Prediction and Classification of Multiple Sclerosis Disease: A Mental Health Disorder
    Vaishali Mehta Wadhwa, Jyoti Garg, Dolly Sharma · 2025 · Communications in computer and information science
  21. Large Language Models for Explainable Medical Text Summarization: A Systematic Literature Review
    Aleka Melese Ayalew, Md Rabiul Hasan, Tapio Seppänen, Mourad Oussalah · 2026 · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
  22. From Black Box to Transparency: Consistency and Cost within XAI
    Júlio Corona, Pedro Rodrigues, Leonardo Almeida, Rafael Teixeira, Mário Antunes, Rui L. Aguiar · 2024 · IEEE Globecom Workshops (GC Wkshps)
  23. Technologies to Assist Students with Specific Learning Disabilities in Higher Education: Concepts, Challenges and Future Directions
    Dasaradharami Reddy Kandati, S Anusha, Azham Hussain · 2024 · Applied Intelligence and Informatics.
  24. An in-depth analysis of KernelSHAP and SamplingSHAP: assessing robustness, error, and efficiency
    Beyza Aydoğan, Tevfik Aytekin · 2025 · Knowledge and Information Systems
  25. Enhancing Fan Base Engagement through Explainable Self-Learning Sentiment Analysis
    M. H. Lye, Nethmi Wijesinghe · 2024 · Moratuwa Engineering Research Conference (MERCon)
  26. Exploring Explainable AI Techniques for Text Classification in Healthcare: A Scoping Review
    Ibrahim Alaa eddine Madi, Akram Redjdal, Jacques Bouaud A, Brigitte Séroussi A · 2024 · Studies in health technology and informatics
  27. How to improve PHEV electric mileage ratios? Factor decomposition with Explainable AI
    Hayato Goto, Tomoki Nishi, Takahiro Shiga, Takeyuki Sasai, Shintaro Fukushima · 2025 · Transportation Research Part D Transport and Environment
  28. Explainable AI for Bipolar Disorder Diagnosis Using Hjorth Parameters
    Mehrnaz Saghab Torbati, Ahmad Zandbagleh, Mohammad Reza Daliri, Amirmasoud Ahmadi, Reza Rostami, Reza Kazemi · 2025 · Diagnostics
  29. Lower and upper bound estimation (LUBE) for predicting the surface water quality in the lower Mun river basin using machine learning algorithms
    Chawisa Chawishborwornworng, Monchai Chansiri, Santamon Luanwuthi · 2025 · Modeling Earth Systems and Environment
  30. How to Measure Explainability and Interpretability of Machine Learning Results
    Elisabeth Mayrhuber, Bogdan Burlacu, Stephan Winkler · 2025 · Genetic and evolutionary computation
  31. Smart driving with AI: A review of CNN approaches to drowsiness detection
    Riadul Islam Rabbi, Poh Ping Em, Md. Jakir Hossen · 2025 · Array
  32. Requirements Driven Explainable Artificial Intelligence Framework for Secure and Transparent Clinical Decision Support Systems
    Mobeen Nazar, Salahuddin Unar, Anil Ahmed, Mazliham Mohd Su’ud, Mansoor Alam, Azizah Rahmat · 2026 · IEEE Access
  33. A Comparative Exploration of SHAP and LIME for Enhancing the Interpretability of Machine Learning Models in Obesity Prediction
    Olushina Olawale Awe, Joshua Salako, Paulo Canas Rodrigues, Natisha Dukhi, Ronaldo Dias · 2024 · STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health
  34. Synergistic AI for Nuclear Safety: PINNs, XAI, DTs, and LLMs in Fault Diagnosis
    Ben Qi, Xingyu Xiao, Jingang Liang · 2026 · Nuclear Technology
  35. Empowering Breast Cancer Diagnostics: SHAP-Enhanced Explainable AI
    Zulfikar Ali Ansari, Rafeeq Ahmed, Manish Madhava Tripathi, Nafees Akhter Farooqui, Md Shamsul Haque Ansari, Shadab Siddiqui, Shahin Fatima · 2025 · Artificial intelligence-enhanced software and systems engineering
  36. The Wildcard XAI: from a Necessity, to a Resource, to a Dangerous Decoy
    Rachele Carli, Davide Calvaresi · 2024 · Lecture notes in computer science
  37. Intelligent Adaptive Systems
    George Margetis, Stavroula Ntoa, Constantine Stephanidis · 2025 · Springer eBooks
  38. A No Code XAI Framework for Policy Making
    Marta Patiño-Martı́nez, Ainhoa Azqueta-Alzúaz · 2023 · International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)
  39. Integrating Shapley Value and Least Core Attribution for Robust Explainable AI in Rent Prediction
    Xinyu Wang, Tris Kee · 2025 · Buildings
  40. A machine learning approach for determining solitary pulmonary nodule malignancy in patients undergoing PET/CT examination
    Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos · 2025 · Multimedia Tools and Applications
  41. Enhancing agricultural data interpretability and visualization with TabNet-driven feature extraction and Local Biplots
    Jenniffer Carolina Triana-Martinez, Andrés Marino Álvarez-Meza, German Castellanos-Dominguez · 2025 · Results in Engineering
  42. Through the Thicket: A Study of Number-Oriented LLMS Derived from Random Forest Models
    Michał Romaszewski, Przemysław Sekuła, Przemysław Głomb, Michał Cholewa, Katarzyna Kołodziej · 2025 · Journal of Artificial Intelligence and Soft Computing Research
  43. Integrating explainable machine learning models for interpreting edm performance in inconel 718 with cryogenically treated electrodes
    Elumalai Boominathan, K. Giridharan, Praveen Kumar Alagesan · 2025 · The International Journal of Advanced Manufacturing Technology
  44. Integrating artificial intelligence with small molecule therapeutics and precision medicine for neurochemical understanding of Alzheimer’s diseases
    Zafer Saad Alshehri · 2025 · Neuroscience
  45. Inside the black box: A comprehensive survey of explainable AI benchmarks, protocols, technical analysis, and open gaps
    Habib Khan, Faleh AlQahtani, Weiwei Jiang, Muhammad Hamza Ali, Sareer Ul Amin, JaKeoung Koo · 2026 · Computer Science Review
  46. FACEGroup: Feasible and Actionable Counterfactual Explanations for Group Fairness
    Christos Fragkathoulas, Vasiliki Papanikou, Evaggelia Pitoura, Evimaria Terzi · 2025 · Lecture notes in computer science
  47. Combining SHAP-Driven Co-clustering and Shallow Decision Trees to Explain XGBoost
    Ruggero G. Pensa, Anton Crombach, Sergio Peignier · 2025 · Lecture notes in computer science
  48. AI in flow cytometry: Current applications and future directions
    Alice Yue, Ryan R. Brinkman, Veronica Nash, Fabian Junker, Goce Bogdanoski, Anagha Divekar, Aaron J. Tyznik, Josef Špidlen, Wolfgang Kern, Jordi Pétriz et al. · 2025 · Cytometry Part B Clinical Cytometry
  49. fiXAIt: A novel feature importance-based XAI tool for enhanced explainability, self-consistency, and computational efficiency
    Selman Uzun, Güngör Yıldırım · 2025 · Applied Soft Computing
  50. Merging multimodal digital biomarkers into “Digital Neuro Fingerprints” for precision neurology in dementias: the promise of the right treatment for the right patient at the right time in the age of AI
    Ioannis Tarnanas, Azizi A Seixas, Martin Wyss, Panagiotis Vlamos, Arzu Çöltekin · 2026 · Frontiers in Digital Health
  51. Explainable Artificial Intelligence for Crowd Forecasting Using Global Ensemble Echo State Networks
    Chamod Damitha Samarajeewa, Daswin De Silva, Milos Manic · 2024 · IEEE Open Journal of the Industrial Electronics Society
  52. Privacy Preservation with Noise in Explainable AI
    Sonal Allana, Rozita A. Dara · 2025 · Conference on Privacy, Security and Trust
  53. Minimizing Model Misclassification Using Regularized Loss Interpretability
    Elyes Manai, Mohamed Mejri, Jaouhar Fattahi · 2024 · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
  54. Can explainable artificial intelligence support software modelers in model comprehension?
    Francisco Javier Alcaide, José Raúl Romero, Aurora Ramírez · 2025 · Software & Systems Modeling
  55. Transparency is Crucial for User-Centered AI, or is it? How this Notion Manifests in the UK Press Coverage of GPT
    Mariavittoria Masotina, Elena Musi, Anna Spagnolli · 2023 · Biannual Conference of the Italian SIGCHI Chapter (CHItaly)
  56. Pixel-Based Clustering for Local Interpretable Model-Agnostic Explanations
    Junyan Qian, Tong Wen, Ming Ling, Xiaofu Du, Hao Ding · 2025 · Journal of Artificial Intelligence and Soft Computing Research
  57. Defending Against AI Threats with a User-Centric Trustworthiness Assessment Framework
    Efi Kafali, Davy Preuveneers, Theodoros Semertzidis, Petros Daras · 2024 · Big Data and Cognitive Computing
  58. Transformative Advances in PET Imaging: From FDG to Total Body Scanners, Novel Tracers and AI-Driven Precision Medicine
    Praveen Gurunath Bharathi, Shiva Abbaszadeh, Paweł Moskal, Abass A. Alavi · 2025 · Bio-Algorithms and Med-Systems
  59. Enhancing User Acceptance of an AI Agent’s Recommendation in Information-Sharing Environments
    Rebecca Kehat, Ron S. Hirschprung, Shani Alkoby · 2024 · Applied Sciences
  60. Standardization of Neuromuscular Reflex Analysis—Role of Fine-Tuned Vision-Language Model Consortium and OpenAI gpt-oss Reasoning LLM-Enabled Decision Support System
    Eranga Bandara, Ross Joseph Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva et al. · 2026 · Biomechanics
  61. Leveraging Large Language Models to Enhance Domain Expert Inclusion in Data Science Workflows
    Jasmine Y. Shih, Vishal Mohanty, Yannis Katsis, Hariharan Subramonyam · 2024 · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA)
  62. Explainable AI for Real-Time Object Detection in Autonomous Driving
    Tayyab Sajid, Omar Abdul Latif · 2024 · International Conference on Artificial Intelligence, Metaverse and Cybersecurity (ICAMAC)
  63. Nine quick tips for trustworthy machine learning in the biomedical sciences
    Luca Oneto, Davide Chicco · 2025 · PLoS Computational Biology
  64. XAG: Enhancing Transparency by Integrating Explainable Artificial Intelligence with Large Language Models
    Takafumi Nakanishi · 2024 · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
  65. PRIME: A Multi-Agent Environment for Orchestrating Dynamic Computational Workflows in Protein Engineerings
    Yuyang Zhou, Jin Su, Jiawei Zhang, Wangyang Hu, Tianli Tao, Guanqi Li, Xibin Zhou, Li Fan, Fajie Yuan · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  66. Large Language Model Reasoning Failures
    Song, Peiyang, Han, Pengrui, Goodman, Noah · 2026 · arXiv
  67. FaceOracle: Chat with a Face Image Oracle
    Wassim Kabbani, Kiran B. Raja, Raghavendra Ramachandra, Christoph Busch · 2025 · Lecture notes in computer science
  68. A Statistical‐Process Hybridized Approach to Modeling Permafrost Distribution in a Boreal Wetland Ecosystem, Whatì, NT, Canada
    Philip P. Bonnaventure, Sophie MacLean, Nick C. Noad, Madeleine C. Garibaldi · 2026 · Permafrost and Periglacial Processes
  69. Explain it like I'm me: User Characteristics in XAI Decision-Making
    Malik Khadar, Amoligha Timma, Luka Ludden, Harmanpreet Kaur · 2025 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
  70. FedXAI for Detecting DDoS on IoT Edge Networks in Federated Learning
    Ahmed Asiri, Weiqi Wang, Feng He Wu, Hiep Khac Vo, Shui Yu · 2024 · International Telecommunication Networks and Applications Conference (ITNAC)
  71. Towards Explainable Decision Support in Demand Forecasting: Global Feature Importance for Multi-Series Tree-Based Models
    Mátyás Kuti-Kreszács, Laura Diosan, Zalán Bodó · 2026 · Acta Universitatis Sapientiae Informatica
  72. How Well do LLMs Assist Parents in Assessing Child Appropriateness of Videos?
    Sabila Nawshin, Ashley Phoebe Ishoel, Arun Balaji Buduru, Apu Chandrasen Kapadia · 2026 · CHI Conference on Human Factors in Computing Systems
  73. Detecting Gender Stereotype Biases Against Women Entrepreneurs in Large Language Models
    Xian Cao, Hongfei Li, Qingyu Xu, Ruoqing Zhu · 2025 · Journal of Business Ethics
  74. Explainable Artificial Intelligence for Deepfake Detection: Pipeline, Open Source and Comparisons
    Hao Li, Junxin Chen, Bo Wang, Salvador García, David Camacho · 2026 · Expert Systems
  75. Recovering Traceability Links Between Code and Documentation: A Retrospective
    Giuliano Antoniol, Gerardo Canfora, Gerardo Casazza, Andrea De Lucia, Ettore Merlo · 2025 · IEEE Transactions on Software Engineering
  76. Explaining Tourism Expenditure Patterns in Italy: A Comparative Study of Domestic and Incoming Tourists Using XGBoost and SHAP
    Fabrizio Antolini, Samuele Cesarini, Ivan Terraglia · 2025 · Social Indicators Research
  77. Explaining the Unexplainable: A Systematic Review of Explainable AI in Finance
    Md Talha Mohsin, Nabid Bin Nasim · 2025 · SSRN Electronic Journal
  78. Explainability, fairness and the Simpson’s paradox in credit lending
    Golnoosh Babaei, Paolo Giudici, Parvati Neelakantan · 2025 · Physica A Statistical Mechanics and its Applications
  79. Toward Anomaly Detection Using Explainable AI
    Manh-Dung Nguyen, Vinh-Hoa La, Wissam Mallouli · 2023 · Springer eBooks
  80. Enhancing Explainability and Reliable Decision-Making in Particle Swarm Optimization through Communication Topologies
    Nitin Gupta, Indu Bala, Bapi Dutta · 2025 · Genetic and Evolutionary Computation Conference Companion (GECCO Companion)
  81. Interpretability Index Based on Balanced Volumes for Transparent Models and Agnostic Explainers
    Daniel Furtado Leite, Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo · 2024 · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
  82. Introduction to artificial intelligence in multi-omics analysis
    Arpan Saha, Rajat Kumar Pal, Sudipto Saha · 2026 · Progress in molecular biology and translational science
  83. An Explainable Machine Learning Approach for Early Prediction of Gestational Diabetes Mellitus (GDM)
    Muhammad Aatif, Ihtesham Ul Islam, Naima Iltaf, Hammad Afzal · 2025 · Communications in computer and information science
  84. Future-proof learning: redesigning ADDIE for Generation Alpha with explainable AI and human-computer integration
    Nurdayana Mohamad Noor · 2026 · AAOU Journal/AAOU journal
  85. Tobacco cultivation in Yunnan: an integrated analysis of economic trends and diversification
    Jie Song, Jiang Wu, Xiangyang Li et al. · 2026 · Frontiers in Sustainable Food Systems
  86. Passenger Switch Behavior and Decision Mechanisms in Multimodal Public Transportation Systems
    Zhe Zhang, Wenxie Lin, Tongyu Hu · 2025 · Systems
  87. FedXChain: Explainable Federated Learning with Adaptive Trust Scoring and Blockchain-Based Audit Trails
    Rachmad Andri Atmoko, Sholeh Hadi Pramono, Muhammad Fauzan Edy Purnomo, Panca Mudjirahardjo, Mahdin Rohmatillah, Cries Avian · 2026 · Engineering Technology & Applied Science Research
  88. Explainable Deep-Learning-Based Adversarial Defense for Automatic Modulation Classification
    Peihao Dong, Jingchun Wang, Shen Gao · 2025 · IEEE Internet of Things Journal
  89. Document structure-driven investigative information retrieval
    Tuomas Ketola, Thomas Roelleke · 2023 · Information Systems
  90. Beyond the alarm: proactive predictions for cardiac arrest incidents in hospitals using Interpretable machine learning models
    Antra, U. Dinesh Kumar, Gaurav Loria, Yogamaya Nayak · 2024 · Journal of the Operational Research Society
  91. Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments
    Stefan Haas, Konstantin Hegestweiler, Michael T. Rapp, Maximilian Muschalik, Eyke Hüllermeier · 2024 · Frontiers in Artificial Intelligence
  92. The responsibility to inform: How AI companies’ transparent communication practice influences public readiness in a cross-national context
    Hao Xu, Chuqing Dong · 2026 · Communication and Change
  93. Challenges in Developing Ethical and Socially Responsible Explainable AI
    Md. Amir Khusru Akhtar, Mohit Kumar, Anand Nayyar · 2024 · Studies in systems, decision and control
  94. The good, the bad and the ugly in artificial intelligence
    Domingo Mery, Gabriela Arriagada-Bruneau, Jocelyn Dunstan · 2026 · AI and Ethics
  95. My digital mentor: a mixed-methods study of user-GAI interactions
    Lei Xian, Guangqiu Cao, Na Zhang · 2025 · Frontiers in Psychology
  96. Facilitating Precision Medicine in HCC Patients by Deep Learning–Directed lncRNAs Classification and Ascertaining Causal Markers
    Rashi Jain, Sathish Kumar Mungamuri, Prabha Garg · 2025 · The Journal of Gene Medicine
  97. Grad-CAM-Driven Explainable Deep Learning Framework for Cervical Cancer Image Classification
    Huynh-Dai-Nhan Tran, Trong-Thang Pham, Manh-Hung Trinh, Tan-Nguyen Ngo, TT Nguyen, Hoang-Anh Pham · 2025 · Lecture notes in computer science
  98. Towards Understandable Transparency in Human-Robot-Interactions in Public Spaces
    André Helgert, Lukas Erle, Sabrina Langer, Carolin Straßmann, Sabrina Cornelia Eimler · 2024 · IEEE RO-MAN
  99. Explainable visual question answering: A survey on methods, datasets and evaluation
    Yaxian Wang, Qi-Ka Lin, Jiang-Bo Shi, Yi-Sheng An, Jun Liu, Bi-Fan Wei, Xudong Jiang · 2026 · Information Fusion
  100. Human-Centered AI for Migrant Integration Through LLM and RAG Optimization
    Dagoberto Castellanos–Nieves, Luis García-Forte · 2024 · Applied Sciences