Check computer science papers: citations, claims and retractions

A systematic review on the use of explainability in deep learning systems for computer aided diagnosis in radiology: Limited use of explainable AI?

Groen, A. M., Kraan, R., Amirkhan, S. F., Daams, J. G., & Maas, M. (2022) · European Journal of Radiology

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 89

Making the Transition to E-Learning: Strategies and Issues

Bullen, M. (2007) · IGI Global eBooks

Educational Technology and E-LearningOnline and Blended Learning

Cited by 89

Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Huang, X., Lian, J., Lei, Y., Yao, J., Lian, D., & Xie, X. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 89

Cultural heritage, tourist attractiveness and augmented reality: insights from Italy

Graziano, T., & Privitera, D. (2020) · Journal of Heritage Tourism

Augmented Reality ApplicationsDiverse Aspects of Tourism Research

Cited by 89

The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates

Schuller, B. W., Batliner, A., Bergler, C., Mascolo, C., Han, J., Lefter, I., Kaya, H., Amiriparian, S., Baird, A., Stappen, L., et al. (2021) · Interspeech 2021

Speech Recognition and SynthesisEmotion and Mood Recognition

Cited by 89

Can Better Identifier Splitting Techniques Help Feature Location?

Dit, B., Guerrouj, L., Poshyvanyk, D., & Antoniol, G. (2011) · 2011 IEEE 19th International Conference on Program Comprehension

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 89

Integrating an Unsupervised Transliteration Model into Statistical Machine Translation

Durrani, N., Sajjad, H., Hoang, H., & Koehn, P. (2014) · Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers

Natural Language Processing TechniquesSpeech Recognition and Synthesis

Cited by 89

Providing End-to-End Security Using Quantum Walks in IoT Networks

El-Latif, A. A. A., Abd-El-Atty, B., Venegas-Andraca, S. E., Elwahsh, H., Piran, M. J., Bashir, A. K., Song, O.-Y., & Mazurczyk, W. (2020) · IEEE Access

Chaos-based Image/Signal EncryptionQuantum Information and Cryptography

Cited by 89

Learning to dress: Synthesizing human dressing motion via deep reinforcement learning

Clegg, A., Yu, W., Tan, J., Liu, C. K., & Turk, G. (2018) · ACM Transactions on Graphics

Reinforcement Learning in RoboticsHuman Motion and Animation

Cited by 89

Reward has a residual impact on target selection in visual search, but not on the suppression of distractors

Hickey, C., Chelazzi, L., & Theeuwes, J. (2011) · Visual Cognition

Visual Attention and Saliency DetectionVisual perception and processing mechanisms

Cited by 89

A Survey of Transfer and Multitask Learning in Bioinformatics

Xu, Q., & Yang, Q. (2011) · Journal of Computing Science and Engineering

Domain Adaptation and Few-Shot LearningMachine Learning in Bioinformatics

Cited by 89

Understanding Error Propagation in GPGPU Applications

Li, G., Pattabiraman, K., Cher, C.-Y., & Bose, P. (2016) · SC16: International Conference for High Performance Computing, Networking, Storage and Analysis

Distributed systems and fault toleranceParallel Computing and Optimization Techniques

Cited by 89

Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models

Röttger, P., Hofmann, V., Pyatkin, V., Hinck, M., Kirk, H., Schuetze, H., & Hovy, D. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 89

Modern Artificial Intelligence Model Development for Undergraduate Student Performance Prediction: An Investigation on Engineering Mathematics Courses

Deo, R. C., Yaseen, Z. M., Al-Ansari, N., Nguyen-Huy, T., Langlands, T. A. M., & Galligan, L. (2020) · IEEE Access

Online Learning and AnalyticsMachine Learning and ELM

Cited by 89

MovingPandas: Efficient Structures for Movement Data in Python

Graser, A. (2019) · GI_Forum

Data Management and AlgorithmsComputational Physics and Python Applications

Cited by 89

The Attraction Effect in Information Visualization

Dimara, E., Bezerianos, A., & Dragicevic, P. (2017) · IEEE Transactions on Visualization and Computer Graphics

Data Visualization and AnalyticsDecision-Making and Behavioral Economics

Cited by 89

Decision level combination of multiple modalities for recognition and analysis of emotional expression

Metallinou, A., Lee, S., & Narayanan, S. (2010) · 2010 IEEE International Conference on Acoustics, Speech and Signal Processing

Emotion and Mood RecognitionFace and Expression Recognition

Cited by 89

A systematic review of comparative evidence of aspect-oriented programming

Ali, M. S., Ali Babar, M., Chen, L., & Stol, K.-J. (2010) · Information and Software Technology

Advanced Software Engineering MethodologiesSoftware Engineering Techniques and Practices

Cited by 89

Tapping into the wisdom of the crowd—with confidence

Hertwig, R. (2012) · Science

Mobile Crowdsensing and CrowdsourcingDecision-Making and Behavioral Economics

Cited by 89

When deep learning meets edge computing

Huang, Y., Ma, X., Fan, X., Liu, J., & Gong, W. (2017) · 2017 IEEE 25th International Conference on Network Protocols (ICNP)

IoT and Edge/Fog ComputingEnergy Efficiency in Computing

Cited by 89

Self-Reflection in LLM Agents: Effects on Problem-Solving Performance

Renze, M., & Guven, E. (2024) · arXiv

Topic ModelingAI-based Problem Solving and Planning

Cited by 89

Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Huang, X., Lian, J., Lei, Y., Yao, J., Lian, D., & Xie, X. (2025) · ACM Transactions on Information Systems

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 89

Proof-of-Personhood: Redemocratizing Permissionless Cryptocurrencies

Borge, M., Kokoris-Kogias, E., Jovanovic, P., Gasser, L., Gailly, N., & Ford, B. (2017) · 2017 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

Blockchain Technology Applications and SecurityCryptography and Data Security

Cited by 89

Who is peeping at your passwords at Starbucks? — To catch an evil twin access point

Song, Y., Yang, C., & Gu, G. (2010) · 2010 IEEE/IFIP International Conference on Dependable Systems & Networks (DSN)

Network Security and Intrusion DetectionWireless Networks and Protocols

Cited by 89