Check computer science papers: citations, claims and retractions

Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence

Feng, S., Wang, Z., Wang, Y., Ebrahimi, S., Palangi, H., Miculicich, L., Kulshrestha, A., Rauschmayr, N., Choi, Y., Tsvetkov, Y., et al. (2024) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 24

Federated learning as a smart tool for research on infectious diseases

Zwiers, L. C., Grobbee, D. E., Uijl, A., & Ong, D. S. Y. (2024) · BMC Infectious Diseases

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 24

GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations

Yang, J., Lai, K.-H., Wang, X., Chang, S., Harari, Y., & Gabrilovich, E. (2026) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 24

Mandatory data and code sharing for research published by The BMJ

Loder, E., Macdonald, H., Bloom, T., & Abbasi, K. (2024) · BMJ

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 24

JustCorrect: Intelligent Post Hoc Text Correction Techniques on Smartphones

Cui, W., Zhu, S., Zhang, M. R., Schwartz, H. A., Wobbrock, J. O., & Bi, X. (2020) · Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

Usability and User Interface DesignInteractive and Immersive Displays

Cited by 24

Malicious practice of fake reviews: experimental insight into the potential of contextual indicators in assisting consumers to detect deceptive opinion spam

Munzel, A. (2015) · Recherche et Applications en Marketing (English Edition)

Spam and Phishing DetectionDigital Marketing and Social Media

Cited by 24

Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation

Rebuffel, C., Scialom, T., Soulier, L., Piwowarski, B., Lamprier, S., Staiano, J., Scoutheeten, G., & Gallinari, P. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 24

InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning

Yang, Y., Tang, Y., & Tam, K. Y. (2023) · arXiv

Topic ModelingStock Market Forecasting Methods

Cited by 24

CitePrompt: Using Prompts to Identify Citation Intent in Scientific Papers

Lahiri, A., Sanyal, D. K., & Mukherjee, I. (2023) · 2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

Topic Modelingscientometrics and bibliometrics research

Cited by 24

Precise synchronization time stamp generation for Bluetooth low energy

Rheinlander, C. C., & Wehn, N. (2016) · 2016 IEEE SENSORS

Bluetooth and Wireless Communication TechnologiesNetwork Time Synchronization Technologies

Cited by 24

The Subjects and Stages of AI Dataset Development: A Framework for Dataset Accountability

Khan, M., & Hanna, A. (2022) · SSRN Electronic Journal

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 24

Treatment effect prediction with adversarial deep learning using electronic health records

Chu, J., Dong, W., Wang, J., He, K., & Huang, Z. (2020) · BMC Medical Informatics and Decision Making

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 24

Quantum Computer-Aided design of Quantum Optics Hardware

Kottmann, J. S., Krenn, M., Kyaw, T. H., Alperin-Lea, S., & Aspuru-Guzik, A. (2020) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 24

Exploration of technical debt in start-ups

Klotins, E., Unterkalmsteiner, M., Chatzipetrou, P., Gorschek, T., Prikladnicki, R., Tripathi, N., & Pompermaier, L. B. (2018) · Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 24

How New Technologies Spread: Lessons from Computing Technologies

Cortada, J. W. (2013) · Technology and Culture

History of Computing TechnologiesInnovation Diffusion and Forecasting

Cited by 24

MIMIC-III Clinical Database Demo

Johnson, A., Pollard, T., & Mark, R. (2019) · PhysioNet

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 24

Semantic Exploration from Language Abstractions and Pretrained Representations

Tam, A. C., Rabinowitz, N. C., Lampinen, A. K., Roy, N. A., Chan, S. C. Y., Strouse, D., Wang, J. X., Banino, A., & Hill, F. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 24

Visual Debugging Techniques for Reactive Data Visualization

Hoffswell, J., Satyanarayan, A., & Heer, J. (2016) · Computer Graphics Forum

Data Visualization and AnalyticsComputer Graphics and Visualization Techniques

Cited by 24

Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism

Mallari, K., Inkpen, K., Johns, P., Tan, S., Ramesh, D., & Kamar, E. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AICriminal Justice and Corrections Analysis

Cited by 24

AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models

Yin, Y., Chen, C., Shang, L., Jiang, X., Chen, X., & Liu, Q. (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)

Topic ModelingMachine Learning and Data Classification

Cited by 24

Generalized genomic data sharing for differentially private federated learning

Aziz, M. M. A., Anjum, M. M., Mohammed, N., & Jiang, X. (2022) · Journal of Biomedical Informatics

Privacy-Preserving Technologies in DataCloud Data Security Solutions

Cited by 24

A Semantic-Enhanced Method Based On Deep SVDD for Pixel-Wise Anomaly Detection

Hu, C., Chen, K., & Shao, H. (2021) · 2021 IEEE International Conference on Multimedia and Expo (ICME)

Anomaly Detection Techniques and ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 24

Hypothesis Transfer Learning for Efficient Data Computing in Smart Cities Environments

Valerio, L., Passarella, A., & Conti, M. (2016) · 2016 IEEE International Conference on Smart Computing (SMARTCOMP)

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 24

Differential Privacy Defenses and Sampling Attacks for Membership Inference

Rahimian, S., Orekondy, T., & Fritz, M. (2021) · Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 24