Check computer science papers: citations, claims and retractions

Benchmarking Machine Learning Solutions in Production

Cardoso Silva, L., Rezende Zagatti, F., Silva Sette, B., Nildaimon dos Santos Silva, L., Lucredio, D., Furtado Silva, D., & de Medeiros Caseli, H. (2020) · 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 33

Towards shaping the future of responsible AI in africa

Eke, D. O., Chintu, S. S., & Wakunuma, K. (2023) · Social and Cultural Studies of Robots and AI

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 33

ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation

Xia, F., Li, C., Martín-Martín, R., Litany, O., Toshev, A., & Savarese, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 33

Optimized Convolutional Neural Network at the IoT edge for image detection using pruning and quantization

Naveen, S., & Kounte, M. R. (2024) · Multimedia Tools and Applications

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 33

Automatic Passenger Counting System Using Image Processing Based on Skin Colour Detection Approach

Nasir, A. S. A., Gharib, N. K. A., & Jaafar, H. (2018) · 2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 33

Flow-of-action: SOP-enhanced LLM-based multi-agent system for root cause analysis

Pei, C., Wang, Z., Liu, F., Li, Z., Liu, Y., He, X., Kang, R., Zhang, T., Chen, J., Li, J., et al. (2025) · Companion Proceedings of the ACM on Web Conference 2025

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 33

Clinical Reading Comprehension: A Thorough Analysis of the emrQA Dataset

Yue, X., Jimenez Gutierrez, B., & Sun, H. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 33

Foundations of Differentially Oblivious Algorithms

Chan, T.-H. H., Chung, K.-M., Maggs, B. M., & Shi, E. (2019) · Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms

Cryptography and Data SecurityPrivacy-Preserving Technologies in Data

Cited by 33

Reversible universal quantum computation within translation-invariant systems

Vollbrecht, K. G. H., & Cirac, J. I. (2006) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 33

Measuring Faithfulness in Chain-of-Thought Reasoning

Lanham, T., Chen, A., Radhakrishnan, A., Steiner, B., Denison, C., Hernandez, D., Li, D., Durmus, E., Hubinger, E., Kernion, J., et al. (2023) · arXiv

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 33

Intrinsic bias metrics do not correlate with application bias

Goldfarb-Tarrant, S., Marchant, R., Muñoz Sánchez, R., Pandya, M., & Lopez, A. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 33

Reinforcement Learning with an Ensemble of Binary Action Deep Q-Networks

M. Hafiz, A., Hassaballah, M., Alqahtani, A., Alsubai, S., & Abdel Hameed, M. (2023) · Computer Systems Science and Engineering

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 33

Knowledge Engineering: Building Cognitive Assistants for Evidence-based Reasoning

Tecuci, G., Marcu, D., Boicu, M., & Schum, D. A. (2016) · Cambridge University Press eBooks

AI-based Problem Solving and PlanningAdvanced Computational Techniques and Applications

Cited by 33

One-Class Knowledge Distillation for Spoofing Speech Detection

Lu, J., Zhang, Y., Wang, W., Shang, Z., & Zhang, P. (2024) · ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 33

Enabling task-level scheduling on heterogeneous platforms

Sun, E., Schaa, D., Bagley, R., Rubin, N., & Kaeli, D. (2012) · Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units

Parallel Computing and Optimization TechniquesEmbedded Systems Design Techniques

Cited by 33

Multi-modal Knowledge-aware Hierarchical Attention Network for Explainable Medical Question Answering

Zhang, Y., Qian, S., Fang, Q., & Xu, C. (2019) · Proceedings of the 27th ACM International Conference on Multimedia

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 33

Licensing Schemes in the Production and Distribution of Open Source Software: An Empirical Investigation

Bonaccorsi, A., & Rossi Lamastra, C. (2003) · SSRN Electronic Journal

Open Source Software InnovationsDigital Platforms and Economics

Cited by 33

Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech

Baider, F. (2023) · Politics and Governance

Hate Speech and Cyberbullying DetectionMisinformation and Its Impacts

Cited by 33

Future Shock: Generative AI and the International AI Policy and Governance Crisis

Leslie, D., & Perini, A. M. (2024) · Harvard Data Science Review

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 33

Appearance Matters, So Does Audio: Revealing the Hidden Face via Cross-Modality Transfer

Kong, C., Chen, B., Yang, W., Li, H., Chen, P., & Wang, S. (2022) · IEEE Transactions on Circuits and Systems for Video Technology

Face recognition and analysisDigital Media Forensic Detection

Cited by 32

A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks

Saunshi, N., Malladi, S., & Arora, S. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 32

Demo abstract: Distributed machine learning at resource-limited edge nodes

Tuor, T., Wang, S., Salonidis, T., Ko, B. J., & Leung, K. K. (2018) · IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 32

Believable and Effective AI Agents in Virtual Worlds: Current State and Future Perspectives

Umarov, I., & Mozgovoy, M. (2012) · International Journal of Gaming and Computer-Mediated Simulations

Artificial Intelligence in GamesSocial Robot Interaction and HRI

Cited by 32

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Zhang, D., Zhoubian, S., Hu, Z., Yue, Y., Dong, Y., & Tang, J. (2024) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 32