Check computer science papers: citations, claims and retractions

XOR-Based FEC to Improve Burst-Loss Tolerance for 8K Ultra-High Definition TV over IP Transmission

Kawamoto, J., & Kurakake, T. (2017) · GLOBECOM 2017 - 2017 IEEE Global Communications Conference

Video Coding and Compression TechnologiesError Correcting Code Techniques

Cited by 10

Manipulation and the AI Act: Large Language Model Chatbots and the Danger of Mirrors

Krook, J. (2025) · arXiv

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 10

What Algorithms can Transformers Learn? A Study in Length Generalization

Zhou, H., Bradley, A., Littwin, E., Razin, N., Saremi, O., Susskind, J., Bengio, S., & Nakkiran, P. (2023) · arXiv

Topic ModelingComputability, Logic, AI Algorithms

Cited by 10

Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Ahn, D., Choi, Y., Yu, Y., Kang, D., & Choi, J. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 10

Generative AI, Plagiarism, and Copyright Infringement in Legal Documents

Cyphert, A. B. (2024) · Minnesota journal of law, science & technology

Law, AI, and Intellectual PropertyArtificial Intelligence in Law

Cited by 10

The Authenticity Gap in Human Evaluation

Ethayarajh, K., & Jurafsky, D. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 10

GPT-4V(ision) is a Generalist Web Agent, if Grounded

Zheng, B., Gou, B., Kil, J., Sun, H., & Su, Y. (2024) · arXiv

Multimodal Machine Learning ApplicationsWeb Data Mining and Analysis

Cited by 10

GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

Zadeh, A. H., Edo, I., Awad, O. M., & Moshovos, A. (2020) · 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 10

What Your Next Check-in Might Look Like: Next Check-in Behavior Prediction

Sun, H., Cao, C., Chu, X., Hu, T., Lu, J., He, L., Wang, Z., He, H., & Xiong, H. (2023) · ACM Transactions on Intelligent Systems and Technology

Data Management and AlgorithmsHuman Mobility and Location-Based Analysis

Cited by 10

Using counterfactual tasks to evaluate the generality of analogical reasoning in large language models

Lewis, M., & Mitchell, M. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10

A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI

El-Sayed, S., Akbulut, C., McCroskery, A., Keeling, G., Kenton, Z., Jalan, Z., Marchal, N., Manzini, A., Shevlane, T., Vallor, S., et al. (2024) · arXiv

Ethics and Social Impacts of AIMisinformation and Its Impacts

Cited by 10

The AI intelligence playbook: Decoding GenAI capabilities for strategic advantage

Campbell, C., Sands, S., Whittaker, L., & Mavrommatis, A. (2026) · Business Horizons

Artificial Intelligence ApplicationsImpact of AI and Big Data on Business and Society

Cited by 10

A New Measurement Method of Iimage Encryption

Yu, X. Y., Zhang, J., Ren, H. E., Li, S., & Zhang, X. D. (2006) · Journal of Physics: Conference Series

Chaos-based Image/Signal EncryptionAdvanced Steganography and Watermarking Techniques

Cited by 10

Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction

Zhang, W., Zhao, S., Meng, F., Wu, S., & Liu, M. (2023) · Proceedings of the 31st ACM International Conference on Multimedia

Human Motion and AnimationHuman Pose and Action Recognition

Cited by 10

Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?

Ren, R., Basart, S., Khoja, A., Gatti, A., Phan, L., Yin, X., Mazeika, M., Pan, A., Mukobi, G., Kim, R. H., et al. (2024) · arXiv

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 10

Towards Autoformalization of Mathematics and Code Correctness: Experiments with Elementary Proofs

Cunningham, G., Bunescu, R. C., & Juedes, D. (2023) · arXiv

Logic, programming, and type systemsMathematics, Computing, and Information Processing

Cited by 10

On the Impact of Calibration Data in Post-training Quantization and Pruning

Williams, M., & Aletras, N. (2023) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 10

Greedy Algorithm Based Deep Learning Strategy for User Behavior Prediction and Decision Making Support

Perichappan, K. A. P. (2018) · Journal of Computer and Communications

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 10

A Multi-Scale A Contrario method for Unsupervised Image Anomaly Detection

Tailanian, M., Muse, P., & Pardo, A. (2021) · 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)

Anomaly Detection Techniques and ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 10

MiSet RFC Standards: Defining a Universal Minimum Set of Standards Required for Reproducibility and Rigor in Research Flow Cytometry Experiments

Lucas, F., Gil‐Pulido, J., LaMacchia, J., Preffer, F., Wallace, P. K., & Lopez, P. (2020) · Cytometry Part A

Research Data Management PracticesScientific Computing and Data Management

Cited by 10

Towards Understanding Successful Novice Example Use in Blocks-Based Programming

Ichinco, M., Harms, K., & Kelleher, C. (2017) · Journal of Visual Languages and Sentient Systems

Teaching and Learning ProgrammingSpreadsheets and End-User Computing

Cited by 10

Adaptive learning anomaly detection and classification model for cyber and physical threats in industrial control systems

Ahmadi‐Assalemi, G., Al‐Khateeb, H., Benson, V., Adamyk, B., & Ammi, M. (2025) · IET Cyber-Physical Systems: Theory & Applications

Anomaly Detection Techniques and ApplicationsNetwork Security and Intrusion Detection

Cited by 10

Automated Design of Agentic Systems

Hu, S., Lu, C., & Clune, J. (2024) · arXiv

AI-based Problem Solving and PlanningEvolutionary Algorithms and Applications

Cited by 10

ALOHA: an architectural-aware framework for deep learning at the edge

Meloni, P., Loi, D., Deriu, G., Pimentel, A. D., Sapra, D., Moser, B., Shepeleva, N., Conti, F., Benini, L., Ripolles, O., et al. (2018) · Proceedings of the Workshop on INTelligent Embedded Systems Architectures and Applications

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 10