Check computer science papers: citations, claims and retractions

Designing Contestability: Interaction Design, Machine Learning, and Mental Health

Hirsch, T., Merced, K., Narayanan, S., Imel, Z. E., & Atkins, D. C. (2017) · Proceedings of the 2017 Conference on Designing Interactive Systems

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 110

Racial categories in machine learning

Benthall, S., & Haynes, B. D. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIRacial and Ethnic Identity Research

Cited by 110

Roofline: An Insightful Visual Performance Model for Floating-Point Programs and Multicore Architectures

Williams, S., Waterman, A., & Patterson, D. (2009) · Lawrence Berkeley National Laboratory

Parallel Computing and Optimization TechniquesComputer Graphics and Visualization Techniques

Cited by 110

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Garg, S., Tsipras, D., Liang, P., & Valiant, G. (2022) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 110

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Bean, A. M., Kearns, R. O., Romanou, A., Hafner, F. S., Mayne, H., Batzner, J., Foroutan Eghlidi, N., Schmitz, C., Korgul, K., Batra, H., et al. (2025) · Advances in Neural Information Processing Systems 38

Topic ModelingNatural Language Processing Techniques

Cited by 110

Scalable Active Learning for Object Detection

Haussmann, E., Fenzi, M., Chitta, K., Ivanecky, J., Xu, H., Roy, D., Mittel, A., Koumchatzky, N., Farabet, C., & Alvarez, J. M. (2020) · 2020 IEEE Intelligent Vehicles Symposium (IV)

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 110

Comparing Video and Augmented Reality Assistance in Manual Assembly

Loch, F., Quint, F., & Brishtel, I. (2016) · 2016 12th International Conference on Intelligent Environments (IE)

Augmented Reality ApplicationsInteractive and Immersive Displays

Cited by 110

Diversity and language technology: how language modeling bias causes epistemic injustice

Helm, P., Bella, G., Koch, G., & Giunchiglia, F. (2024) · Ethics and Information Technology

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 110

Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment

Chen, H., Yang, B.-W., Qian, L., Meng, Y.-S., Bai, X.-H., Hong, X.-W., He, X., Jiang, M.-J., Yuan, F., Du, Q.-W., et al. (2022) · Radiology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 110

Computational types from a logical perspective

BENTON, P. N., BIERMAN, G. M., & DE PAIVA, V. C. V. (1998) · Journal of Functional Programming

Logic, programming, and type systemsAdvanced Algebra and Logic

Cited by 110

Emotion recognition from single-channel EEG signals using a two-stage correlation and instantaneous frequency-based filtering method

Taran, S., & Bajaj, V. (2019) · Computer Methods and Programs in Biomedicine

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 110

Decision Provenance: Harnessing Data Flow for Accountable Systems

Singh, J., Cobbe, J., & Norval, C. (2019) · IEEE Access

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 110

Learning the natural history of human disease with generative transformers

Shmatko, A., Jung, A. W., Gaurav, K., Brunak, S., Mortensen, L. H., Birney, E., Fitzgerald, T., & Gerstung, M. (2025) · Nature

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 110

CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow

Weinzaepfel, P., Lucas, T., Leroy, V., Cabon, Y., Arora, V., Brégier, R., Csurka, G., Antsfeld, L., Chidlovskii, B., & Revaud, J. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 110

Wrongfully Accused by an Algorithm *

Hill, K. (2022) · Ethics of Data and Analytics

Ethics and Social Impacts of AIFace recognition and analysis

Cited by 110

Designing and Interpreting Probes with Control Tasks

Hewitt, J., & Liang, P. (2019) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 110

CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text

Sinha, K., Sodhani, S., Dong, J., Pineau, J., & Hamilton, W. L. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 110

Simulating quantum dynamics on a quantum computer

Wiebe, N., Berry, D. W., Høyer, P., & Sanders, B. C. (2011) · Journal of Physics A: Mathematical and Theoretical

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 110

Machine Learning at the Edge: A Data-Driven Architecture with Applications to 5G Cellular Networks

Polese, M., Jana, R., Kounev, V., Zhang, K., Deb, S., & Zorzi, M. (2018) · arXiv

IoT and Edge/Fog ComputingSoftware-Defined Networks and 5G

Cited by 110

Multi-Modal Audio, Video and Physiological Sensor Learning for Continuous Emotion Prediction

Brady, K., Gwon, Y., Khorrami, P., Godoy, E., Campbell, W., Dagli, C., & Huang, T. S. (2016) · Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 110

Scalable detection of partial near-duplicate videos by visual-temporal consistency

Tan, H.-K., Ngo, C.-W., Hong, R., & Chua, T.-S. (2009) · Proceedings of the 17th ACM international conference on Multimedia

Video Analysis and SummarizationAdvanced Image and Video Retrieval Techniques

Cited by 110

Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors

Khalid, H., Kim, M., Tariq, S., & Woo, S. S. (2021) · Proceedings of the 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 110

Adoption of artificial intelligence in breast imaging: evaluation, ethical constraints and limitations

Hickman, S. E., Baxter, G. C., & Gilbert, F. J. (2021) · British Journal of Cancer

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 110

Evolution of an artificial neural network based autonomous land vehicle controller

Baluja, S. (1996) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

Evolutionary Algorithms and ApplicationsNeural Networks and Applications

Cited by 110