Check computer science papers: citations, claims and retractions

Research on Deep Learning Automatic Vehicle Recognition Algorithm Based on RES-YOLO Model

Li, Y., Wang, J., Huang, J., & Li, Y. (2022) · Sensors

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 49

Quantifying the effects of local many-qubit errors and nonlocal two-qubit errors on the surface code

Fowler, A. G., & Martinis, J. M. (2014) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 49

Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Li, Z., Li, C., Zhang, M., Mei, Q., & Bendersky, M. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track

Topic ModelingInformation Retrieval and Search Behavior

Cited by 49

Feature selection based on tensor decomposition and object proposal for night-time multiclass vehicle detection

Kuang, H., Chen, L., Chan, L. L. H., Cheung, R. C. C., & Yan, H. (2019) · IEEE Transactions on Systems, Man, and Cybernetics: Systems

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 49

Unintended machine learning biases as social barriers for persons with disabilitiess

Hutchinson, B., Prabhakaran, V., Denton, R., Webster, K., Zhong, Y., & Denuyl, S. (2020) · ACM SIGACCESS Accessibility and Computing

Ethics and Social Impacts of AIDisability Rights and Representation

Cited by 49

Removing Backdoor-Based Watermarks in Neural Networks with Limited Data

Liu, X., Li, F., Wen, B., & Li, Q. (2021) · 2020 25th International Conference on Pattern Recognition (ICPR)

Adversarial Robustness in Machine LearningAdvanced Steganography and Watermarking Techniques

Cited by 49

Quantum algorithms: A survey of applications and end-to-end complexities

Dalzell, A. M., McArdle, S., Berta, M., Bienias, P., Chen, C.-F., Gilyén, A., Hann, C. T., Kastoryano, M. J., Khabiboulline, E. T., Kubica, A., et al. (2023) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 49

Towards the smart sensors based human emotion recognition

Quazi, M. T., Mukhopadhyay, S. C., Suryadevara, N. K., & Huang, Y. M. (2012) · 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 49

Variational Bayesian inference for linear and logistic regression

Drugowitsch, J. (2013) · arXiv

Gaussian Processes and Bayesian InferenceBayesian Methods and Mixture Models

Cited by 49

Towards Continual Knowledge Learning of Language Models

Jang, J., Ye, S., Yang, S., Shin, J., Han, J., Kim, G., Choi, S. J., & Seo, M. (2021) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 49

LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals

Park, J. S., Zou, C. Q., Kamphorst, J., Egan, N., Shaw, A., Hill, B. M., Cai, C., Morris, M. R., Liang, P., Willer, R., et al. (2024) · arXiv

Ethics and Social Impacts of AIComputational and Text Analysis Methods

Cited by 49

PEER: A Collaborative Language Model

Schick, T., Dwivedi-Yu, J., Jiang, Z., Petroni, F., Lewis, P., Izacard, G., You, Q., Nalmpantis, C., Grave, E., & Riedel, S. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities

Parthasarathy, V. B., Zafar, A., Khan, A., & Shahid, A. (2024) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 49

Does BLEU Score Work for Code Migration?

Tran, N., Tran, H., Nguyen, S., Nguyen, H., & Nguyen, T. (2019) · 2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)

Software Engineering ResearchNatural Language Processing Techniques

Cited by 49

Getting a CLUE: A Method for Explaining Uncertainty Estimates

Antorán, J., Bhatt, U., Adel, T., Weller, A., & Hernández-Lobato, J. M. (2021) · Apollo - University of Cambridge Repository

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine Learning

Cited by 49

T-Count Optimization and Reed–Muller Codes

Amy, M., & Mosca, M. (2019) · IEEE Transactions on Information Theory

Quantum Computing Algorithms and ArchitectureCoding theory and cryptography

Cited by 49

Learning Machine Learning with Personal Data Helps Stakeholders Ground Advocacy Arguments in Model Mechanics

Register, Y., & Ko, A. J. (2020) · Proceedings of the 2020 ACM Conference on International Computing Education Research

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 49

Scaling Data-Constrained Language Models

Muennighoff, N., Rush, A. M., Barak, B., Scao, T. L., Piktus, A., Tazi, N., Pyysalo, S., Wolf, T., & Raffel, C. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

Theories of ”gender” in NLP bias research

Devinney, H., Björklund, J., & Björklund, H. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIGender Studies in Language

Cited by 49

Noise2Music: Text-conditioned Music Generation with Diffusion Models

Huang, Q., Park, D. S., Wang, T., Denk, T. I., Ly, A., Chen, N., Zhang, Z., Zhang, Z., Yu, J., Frank, C., et al. (2023) · arXiv

Music and Audio ProcessingMusic Technology and Sound Studies

Cited by 49

Introspective Neural Networks for Generative Modeling

Lazarow, J., Jin, L., & Tu, Z. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 49

Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systems

Xu, Q., Ali, S., & Yue, T. (2023) · ACM Transactions on Software Engineering and Methodology

Network Security and Intrusion DetectionAnomaly Detection Techniques and Applications

Cited by 49

Assessing emotional responses induced in virtual reality using a consumer EEG headset: A preliminary report

Horvat, M., Dobrinic, M., Novosel, M., & Jercic, P. (2018) · 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 49

Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases

Marletta, S., L’Imperio, V., Eccher, A., Antonini, P., Santonicco, N., Girolami, I., Dei Tos, A. P., Sbaraglia, M., Pagni, F., Brunelli, M., et al. (2023) · Pathology - Research and Practice

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 49