Check computer science papers: citations, claims and retractions

RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

Yu, T., Yao, Y., Zhang, H., He, T., Han, Y., Cui, G., Hu, J., Liu, Z., Zheng, H.-T., Sun, M., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsNatural Language Processing Techniques

Cited by 117

AI’s Empathy Gap: The Risks of Conversational Artificial Intelligence for Young Children’s Well-Being and Key Ethical Considerations for Early Childhood Education and Care

Kurian, N. (2025) · Contemporary Issues in Early Childhood

Ethics and Social Impacts of AIChild Development and Digital Technology

Cited by 117

Reward learning from human preferences and demonstrations in Atari

Ibarz, B., Leike, J., Pohlen, T., Irving, G., Legg, S., & Amodei, D. (2018) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 117

Principles and business processes for responsible AI

Clarke, R. (2019) · Computer Law & Security Review

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 117

Deepfake Attacks: Generation, Detection, Datasets, Challenges, and Research Directions

Naitali, A., Ridouani, M., Salahdine, F., & Kaabouch, N. (2023) · Computers

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 117

Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation

Zhao, Z., Chen, J., Zhou, S., He, X., Cao, X., Zhang, F., & Wu, W. (2023) · IEEE Transactions on Knowledge and Data Engineering

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 117

TAMER: Training an Agent Manually via Evaluative Reinforcement

Bradley Knox, W., & Stone, P. (2008) · 2008 7th IEEE International Conference on Development and Learning

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 117

Virtual Training: Learning Transfer of Assembly Tasks

Carlson, P., Peters, A., Gilbert, S. B., Vance, J. M., & Luse, A. (2015) · IEEE Transactions on Visualization and Computer Graphics

Virtual Reality Applications and ImpactsSimulation and Modeling Applications

Cited by 117

Decentralized and Self-Sovereign Identity: Systematic Mapping Study

Cucko, S., & Turkanovic, M. (2021) · IEEE Access

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 117

Optimal Protocols in Quantum Annealing and QAOA Problems

Brady, L. T., Baldwin, C. L., Bapat, A., Kharkov, Y., & Gorshkov, A. V. (2020) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 117

Towards a Unified Multi-Dimensional Evaluator for Text Generation

Zhong, M., Liu, Y., Yin, D., Mao, Y., Jiao, Y., Liu, P., Zhu, C., Ji, H., & Han, J. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 117

Security of Blockchain and AI-Empowered Smart Healthcare: Application-Based Analysis

Alabdulatif, A., Khalil, I., & Saidur Rahman, M. (2022) · Applied Sciences

Blockchain Technology Applications and SecurityInternet of Things and AI

Cited by 117

A stateful intrusion detection system for world-wide web servers

Vigna, G., Robertson, W., Kher, V., & Kemmerer, R. A. (2004) · 19th Annual Computer Security Applications Conference, 2003. Proceedings.

Network Security and Intrusion DetectionWeb Application Security Vulnerabilities

Cited by 117

Diffusion Models, Image Super-Resolution, and Everything: A Survey

Moser, B. B., Shanbhag, A. S., Raue, F., Frolov, S., Palacio, S., & Dengel, A. (2025) · IEEE Transactions on Neural Networks and Learning Systems

Advanced Image Processing TechniquesGenerative Adversarial Networks and Image Synthesis

Cited by 117

Stakeholders in Explainable AI

Preece, A., Harborne, D., Braines, D., Tomsett, R., & Chakraborty, S. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 117

Partial Occlusion Handling for Visual Tracking via Robust Part Matching

Zhang, T., Jia, K., Xu, C., Ma, Y., & Ahuja, N. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition

Video Surveillance and Tracking MethodsAdvanced Image and Video Retrieval Techniques

Cited by 117

Experiments with linear prediction in television

Harrison, C. W. (1952) · Bell System Technical Journal

Video Coding and Compression TechnologiesAdvanced Data Compression Techniques

Cited by 117

Advancing health equity with artificial intelligence

Thomasian, N. M., Eickhoff, C., & Adashi, E. Y. (2021) · Journal of Public Health Policy

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 117

Feeling numb: temperature, but not thermal pain, modulates feeling of body ownership

Kammers, M. P. M., Rose, K., & Haggard, P. (2011) · Neuropsychologia

Virtual Reality Applications and ImpactsTactile and Sensory Interactions

Cited by 117

Fairness and Bias in Algorithmic Hiring: A Multidisciplinary Survey

Fabris, A., Baranowska, N., Dennis, M. J., Graus, D., Hacker, P., Saldivar, J., Zuiderveen Borgesius, F., & Biega, A. J. (2025) · ACM Transactions on Intelligent Systems and Technology

Ethics and Social Impacts of AIAI and HR Technologies

Cited by 117

HeadGAN: One-shot Neural Head Synthesis and Editing

Doukas, M. C., Zafeiriou, S., & Sharmanska, V. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 117

Deep Reinforcement Adversarial Learning Against Botnet Evasion Attacks

Apruzzese, G., Andreolini, M., Marchetti, M., Venturi, A., & Colajanni, M. (2020) · IEEE Transactions on Network and Service Management

Adversarial Robustness in Machine LearningNetwork Security and Intrusion Detection

Cited by 117

Adversarial Threats to DeepFake Detection: A Practical Perspective

Neekhara, P., Dolhansky, B., Bitton, J., & Ferrer, C. C. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 117

RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models

Niu, C., Wu, Y., Zhu, J., Xu, S., Shum, K., Zhong, R., Song, J., & Zhang, T. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 117