Check computer science papers: citations, claims and retractions

FTT-NAS: Discovering Fault-tolerant Convolutional Neural Architecture

Ning, X., Ge, G., Li, W., Zhu, Z., Zheng, Y., Chen, X., Gao, Z., Wang, Y., & Yang, H. (2021) · ACM Transactions on Design Automation of Electronic Systems

Advanced Neural Network ApplicationsRadiation Effects in Electronics

Cited by 20

Automatic evaluation of endometrial receptivity in three-dimensional transvaginal ultrasound images based on 3D U-Net segmentation

Wang, X., Bao, N., Xin, X., Tan, J., Li, H., Zhou, S., & Liu, H. (2022) · Quantitative Imaging in Medicine and Surgery

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 20

WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment

Tang, H., Key, D., & Ellis, K. (2024) · Advances in Neural Information Processing Systems 37

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 20

Spatial Semantic Regularisation for Large Scale Object Detection

Mrowca, D., Rohrbach, M., Hoffman, J., Hu, R., Saenko, K., & Darrell, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 20

Neural network decoder for near-term surface-code experiments

Varbanov, B. M., Serra-Peralta, M., Byfield, D., & Terhal, B. M. (2025) · Physical Review Research

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 20

Smart Congestion Control for Delay- and Disruption Tolerant Networks

Silva, A. P., Obraczka, K., Burleigh, S., & Hirata, C. M. (2016) · 2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)

Opportunistic and Delay-Tolerant NetworksNetwork Traffic and Congestion Control

Cited by 20

Phishing and Social Engineering in the Age of LLMs

Gallagher, S., Gelman, B., Taoufiq, S., Vörös, T., Lee, Y., Kyadige, A., & Bergeron, S. (2024) · Large Language Models in Cybersecurity

Spam and Phishing DetectionCybercrime and Law Enforcement Studies

Cited by 20

E- Assessment with Multiple-Choice Questions: A 5 Year Study of Students’ Opinions and Experience

Babo, R., V. Babo, L., T Suhonen, J., & Tukiainen, M. (2020) · Journal of Information Technology Education: Innovations in Practice

Educational Technology and AssessmentStudent Assessment and Feedback

Cited by 20

Machine Learning Operations

Soh, J., & Singh, P. (2020) · Data Science Solutions on Azure

Software Engineering Techniques and PracticesSoftware System Performance and Reliability

Cited by 20

Differentially Private Federated Learningfor Anomaly Detection in eHealth Networks

Cholakoska, A., Pfitzner, B., Gjoreski, H., Rakovic, V., Arnrich, B., & Kalendar, M. (2021) · Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers

Privacy-Preserving Technologies in DataInternet Traffic Analysis and Secure E-voting

Cited by 20

Fighting deepfakes using body language analysis

Yasrab, R., Jiang, W., & Riaz, A. (2021) · Forecasting

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 20

Overview of the MEDIQA-Chat 2023 Shared Tasks on the Summarization & Generation of Doctor-Patient Conversations

Ben Abacha, A., Yim, W.-W., Adams, G., Snider, N., & Yetisgen, M. (2023) · Proceedings of the 5th Clinical Natural Language Processing Workshop

Speech and dialogue systemsArtificial Intelligence in Healthcare and Education

Cited by 20

Efficient and Controllable Model Compression through Sequential Knowledge Distillation and Pruning

Malihi, L., & Heidemann, G. (2023) · Big Data and Cognitive Computing

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 20

Current challenges in adopting machine learning to critical care and emergency medicine

Kang, C.-Y., & Yoon, J. H. (2023) · Clinical and Experimental Emergency Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 20

Longitudinal Model Shifts of Machine Learning–Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals

Cabanillas Silva, P., Sun, H., Rezk, M., Roccaro-Waldmeyer, D. M., Fliegenschmidt, J., Hulde, N., von Dossow, V., Meesseman, L., Depraetere, K., Stieg, J., et al. (2024) · Journal of Medical Internet Research

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 20

A method of state recognition of dressing clothes based on dynamic state matching

Yamazaki, K., Oya, R., Nagahama, K., & Inaba, M. (2013) · Proceedings of the 2013 IEEE/SICE International Symposium on System Integration

Video Surveillance and Tracking MethodsHuman Pose and Action Recognition

Cited by 20

“You don’t understand me!”: Comparing ASR Results for L1 and L2 Speakers of Swedish

Cumbal, R., Moell, B., Lopes, J., & Engwall, O. (2021) · Interspeech 2021

Speech Recognition and SynthesisPhonetics and Phonology Research

Cited by 20

Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models

Groot, T., & Valdenegro - Toro, M. (2024) · Proceedings of the 4th Workshop on Trustworthy Natural Language Processing (TrustNLP 2024)

Multimodal Machine Learning ApplicationsAdversarial Robustness in Machine Learning

Cited by 20

In-Context Unlearning: Language Models as Few Shot Unlearners

Pawelczyk, M., Neel, S., & Lakkaraju, H. (2023) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 20

TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models

Chu, Z., Chen, J., Chen, Q., Yu, W., Wang, H., Liu, M., & Qin, B. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 20

Estimating and Penalizing Preference Shift in Recommender Systems

Carroll, M., Hadfield-Menell, D., Russell, S., & Dragan, A. (2021) · Fifteenth ACM Conference on Recommender Systems

Recommender Systems and TechniquesEthics and Social Impacts of AI

Cited by 20

Extending Context Window of Large Language Models via Semantic Compression

Fei, W., Niu, X., Zhou, P., Hou, L., Bai, B., Deng, L., & Han, W. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 20

AutoVerus: Automated Proof Generation for Rust Code

Yang, C., Li, X., Misu, M. R. H., Yao, J., Cui, W., Gong, Y., Hawblitzel, C., Lahiri, S., Lorch, J. R., Lu, S., et al. (2025) · Proceedings of the ACM on Programming Languages

Logic, programming, and type systemsSoftware Testing and Debugging Techniques

Cited by 20

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Bai, H., Zhou, Y., Cemri, M., Pan, J., Suhr, A., Levine, S., & Kumar, A. (2024) · Advances in Neural Information Processing Systems 37

Reinforcement Learning in RoboticsIoT and Edge/Fog Computing

Cited by 20