Check computer science papers: citations, claims and retractions

Hidden Incentives for Auto-Induced Distributional Shift

Krueger, D., Maharaj, T., & Leike, J. (2020) · arXiv

Ethics and Social Impacts of AIRecommender Systems and Techniques

Cited by 14

Automated Cyber Threat Sensing and Responding: Integrating Threat Intelligence into Security-Policy-Controlled Systems

Amthor, P., Fischer, D., Kühnhauser, W. E., & Stelzer, D. (2019) · Proceedings of the 14th International Conference on Availability, Reliability and Security

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 14

Can people detect errors in shadows and reflections?

Nightingale, S. J., Wade, K. A., Farid, H., & Watson, D. G. (2019) · Attention, Perception, & Psychophysics

Digital Media Forensic DetectionVisual perception and processing mechanisms

Cited by 14

Emotionally Numb or Empathetic? Evaluating How LLMs Feel Using EmotionBench

Huang, J.-T., Lam, M. H., Li, E. J., Ren, S., Wang, W., Jiao, W., Tu, Z., & Lyu, M. R. (2023) · arXiv

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 14

Jumping through Local Minima: Quantization in the Loss Landscape of Vision Transformers

Frumkin, N., Gope, D., & Marculescu, D. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsStochastic Gradient Optimization Techniques

Cited by 14

MasRouter: Learning to Route LLMs for Multi-Agent Systems

Yue, Y., Zhang, G., Liu, B., Wan, G., Wang, K., Cheng, D., & Qi, Y. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Multi-Agent Systems and NegotiationNatural Language Processing Techniques

Cited by 14

A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning Chains

Jacovi, A., Bitton, Y., Bohnet, B., Herzig, J., Honovich, O., Tseng, M., Collins, M., Aharoni, R., & Geva, M. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 14

Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma

Duschner, N., Baguer, D. O., Schmidt, M., Griewank, K. G., Hadaschik, E., Hetzer, S., Wiepjes, B., Le'Clerc Arrastia, J., Jansen, P., Maass, P., et al. (2023) · JDDG: Journal der Deutschen Dermatologischen Gesellschaft

AI in cancer detectionNonmelanoma Skin Cancer Studies

Cited by 14

A novel method to fabricate micro-gratings applied for deformation measurement around a crack in a thin film

Wu, D., Xie, H., Dai, X., & Wang, R. (2014) · Measurement Science and Technology

Optical measurement and interference techniquesMetal and Thin Film Mechanics

Cited by 14

QCSS: A QoE-Aware Control Plane for Adaptive Streaming Service over Mobile Edge Computing Infrastructures

Zhang, L., Wang, S., & Chang, R. N. (2018) · 2018 IEEE International Conference on Web Services (ICWS)

IoT and Edge/Fog ComputingImage and Video Quality Assessment

Cited by 14

Learning to summarize and answer questions about a virtual robot’s past actions

DeChant, C., Akinola, I., & Bauer, D. (2023) · Autonomous Robots

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 14

Interference and Generalization in Temporal Difference Learning

Bengio, E., Pineau, J., & Precup, D. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 14

Security and Privacy Issues in Smart Healthcare Using Machine-Learning Perspectives

Kumar, A., Gupta, N., Bhasin, P., Chauhan, S., & Bachri, I. (2023) · 6G-Enabled IoT and AI for Smart Healthcare

Network Security and Intrusion DetectionInternet of Things and AI

Cited by 14

Contour tracking using a knowledge-based snake algorithm to construct three-dimensional pharyngeal bolus movement

Chang, M. W., Lin, E., & Hwang, J.-N. (1999) · Dysphagia

Medical Image Segmentation TechniquesDysphagia Assessment and Management

Cited by 14

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning

Sun, Q., Yuan, J., He, S., Guan, X., Yuan, H., Fu, X., Li, J., & Yu, P. S. (2025) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 14

Knowledge Graphing Git Repositories: A Preliminary Study

Zhao, Y., Wang, H., Ma, L., Liu, Y., Li, L., & Grundy, J. (2019) · 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER)

Software Engineering ResearchData Visualization and Analytics

Cited by 14

Understanding Emails and Drafting Responses -- An Approach Using GPT-3

Thiergart, J., Huber, S., & Übellacker, T. (2021) · arXiv

Artificial Intelligence ApplicationsTopic Modeling

Cited by 14

The Bot on Speaking Terms: The Effects of Conversation Architecture on Perceptions of Conversational Agents

Wei, C. Z., Kim, Y.-H., & Kuzminykh, A. (2023) · Proceedings of the 5th International Conference on Conversational User Interfaces

Speech and dialogue systemsAI in Service Interactions

Cited by 14

A New Anti-Jamming Strategy Based on Deep Reinforcement Learning for MANET

Xu, Y., Lei, M., Li, M., Zhao, M., & Hu, B. (2019) · 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)

Mobile Ad Hoc NetworksAdversarial Robustness in Machine Learning

Cited by 14

TextPruner: A Model Pruning Toolkit for Pre-Trained Language Models

Yang, Z., Cui, Y., & Chen, Z. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Advanced Neural Network ApplicationsTopic Modeling

Cited by 14

Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory

Mireshghallah, N., Kim, H., Zhou, X., Tsvetkov, Y., Sap, M., Shokri, R., & Choi, Y. (2023) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 14

Linear Representations of Political Perspective Emerge in Large Language Models

Kim, J., Evans, J., & Schein, A. (2025) · arXiv

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

Cited by 14

Rationales for Sequential Predictions

Vafa, K., Deng, Y., Blei, D., & Rush, A. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 14

Religious diversity education: raising children’s awareness of religious diversity through augmented reality

Li, X.-Z., Chen, C.-C., & Kang, X. (2023) · Humanities and Social Sciences Communications

Augmented Reality ApplicationsReligious Education and Schools

Cited by 14