Most cited computer science papers
- Verified
Virtual Reality for Chronic Pain Management Among Historically Marginalized Populations: Systematic Review of Usability Studies
Dy, M., Olazo, K., Lisker, S., Brown, E., Saha, A., Weinberg, J., & Sarkar, U. (2023) · Journal of Medical Internet Research
Virtual Reality Applications and ImpactsPain Management and Treatment
Cited by 17
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Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions
Cao, S., Zhang, J., Shi, J., Lv, X., Yao, Z., Tian, Q., Hou, L., & Li, J. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023
Topic ModelingInformation Retrieval and Search Behavior
Cited by 17
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Measuring Implicit Bias in Explicitly Unbiased Large Language Models
Bai, X., Wang, A., Sucholutsky, I., & Griffiths, T. L. (2024) · arXiv
Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection
Cited by 17
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A model for detecting faults in build specifications
Sotiropoulos, T., Chaliasos, S., Mitropoulos, D., & Spinellis, D. (2020) · Proceedings of the ACM on Programming Languages
Software Testing and Debugging TechniquesSoftware Engineering Research
Cited by 17
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Multi-Level Encoding and Decoding in a Scalable Photonic Tensor Processor With a Photonic General Matrix Multiply (GeMM) Compiler
Guo, Z., Tait, A. N., Marquez, B. A., Filipovich, M., Morison, H., Prucnal, P. R., Chrostowski, L., Shekhar, S., & Shastri, B. J. (2022) · IEEE Journal of Selected Topics in Quantum Electronics
Neural Networks and Reservoir ComputingPhotonic and Optical Devices
Cited by 17
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General intelligence requires rethinking exploration
Jiang, M., Rocktäschel, T., & Grefenstette, E. (2022) · arXiv
Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning
Cited by 17
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Analysis of Fuzzy Logic Modification for Student Assessment in e-Learning
Wardoyo, R., & Yuniarti, W. D. (2020) · IJID (International Journal on Informatics for Development)
Educational Technology and AssessmentEdcuational Technology Systems
Cited by 17
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Practical Peer Prediction for Peer Assessment
Shnayder, V., & Parkes, D. (2016) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing
Mobile Crowdsensing and CrowdsourcingOnline Learning and Analytics
Cited by 17
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Countering Spoof: Towards Detecting Deepfake with Multidimensional Biological Signals
Jin, X., Ye, D., & Chen, C. (2021) · Security and Communication Networks
Digital Media Forensic DetectionBiometric Identification and Security
Cited by 17
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TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Industry Systems
Kong, Y., Ruan, J., Chen, Y., Zhang, B., Bao, T., Shiwei, S., Qing, D. G., Hu, X., Mao, H., Li, Z., et al. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track
AI-based Problem Solving and PlanningNatural Language Processing Techniques
Cited by 17
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The IntelliJ Platform: A Framework for Building Plugins and Mining Software Data
Kurbatova, Z., Golubev, Y., Kovalenko, V., & Bryksin, T. (2021) · 2021 36th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)
Software Engineering ResearchSoftware Engineering Techniques and Practices
Cited by 17
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Automated Scoring of Chinese Engineering Students’ English Essays
Liu, M., Wang, Y., Xu, W., & Liu, L. (2017) · International Journal of Distance Education Technologies
Educational Technology and AssessmentNatural Language Processing Techniques
Cited by 17
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ConvNextUNet: A small-region attentioned model for cardiac MRI segmentation
Zhang, H., & Cai, Z. (2024) · Computers in Biology and Medicine
Medical Image Segmentation TechniquesAdvanced Neural Network Applications
Cited by 17
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Validation of a free software for unsupervised assessment of abdominal fat in MRI
Maddalo, M., Zorza, I., Zubani, S., Nocivelli, G., Calandra, G., Soldini, P., Mascaro, L., & Maroldi, R. (2017) · Physica Medica
Medical Image Segmentation TechniquesBody Composition Measurement Techniques
Cited by 17
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Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance
Zhang, J., Zhang, J., Pertsch, K., Liu, Z., Ren, X., Chang, M., Sun, S.-H., & Lim, J. J. (2023) · arXiv
Reinforcement Learning in RoboticsRobot Manipulation and Learning
Cited by 17
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Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design Considerations
Cai, Z., Han, A., Zhou, X., Gazulla, E. D., & Peppler, K. (2025) · Proceedings of the 24th Interaction Design and Children
Innovative Human-Technology InteractionChild Development and Digital Technology
Cited by 17
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Survey of Websites and Web Application Security Threats Using Vulnerability Assessment
Appiah, V., Asante, M., Nti, I. K., & Nyarko-Boateng, O. (2019) · Journal of Computer Science
Web Application Security VulnerabilitiesInformation and Cyber Security
Cited by 17
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Complex-valued neural networks for voice anti-spoofing
Müller, N. M., Sperl, P., & Böttinger, K. (2023) · INTERSPEECH 2023
Speech Recognition and SynthesisBiometric Identification and Security
Cited by 17
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Weakly Supervised Learning of Placental Ultrasound Images with Residual Networks
Qi, H., Collins, S., & Noble, A. (2017) · Communications in computer and information science
Medical Image Segmentation TechniquesAdvanced Neural Network Applications
Cited by 17
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AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
Zeng, Y., Wu, Y., Zhang, X., Wang, H., & Wu, Q. (2024) · arXiv
Adversarial Robustness in Machine LearningTopic Modeling
Cited by 17
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Calibration, Entropy Rates, and Memory in Language Models
Braverman, M., Chen, X., Kakade, S. M., Narasimhan, K., Zhang, C., & Zhang, Y. (2019) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 17
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Translating Videos into Synthetic Training Data for Wearable Sensor-Based Activity Recognition Systems Using Residual Deep Convolutional Networks
Fortes Rey, V., Garewal, K. K., & Lukowicz, P. (2021) · Applied Sciences
Context-Aware Activity Recognition SystemsPhysical Activity and Health
Cited by 17
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Fault-Tolerant Privacy-Preserving Data Aggregation for Smart Grid
Liu, H., Gu, T., Liu, Y., Song, J., & Zeng, Z. (2020) · Wireless Communications and Mobile Computing
Cryptography and Data SecuritySmart Grid Security and Resilience
Cited by 17
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Peripheral Developer Participation in Open Source Projects: An Empirical Analysis
Krishnamurthy, R., Jacob, V., Radhakrishnan, S., & Dogan, K. (2016) · ACM Transactions on Management Information Systems
Open Source Software InnovationsSoftware Engineering Techniques and Practices
Cited by 17
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