Check computer science papers: citations, claims and retractions

Development and Evaluation of Search Tasks for IIR Experiments using a Cognitive Complexity Framework

Kelly, D., Arguello, J., Edwards, A., & Wu, W.-C. (2015) · Proceedings of the 2015 International Conference on The Theory of Information Retrieval

Information Retrieval and Search BehaviorUsability and User Interface Design

Cited by 155

Consistency Models

Song, Y., Dhariwal, P., Chen, M., & Sutskever, I. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning

Cited by 155

Improving the ratio of memory operations to floating-point operations in loops

Carr, S., & Kennedy, K. (1994) · ACM Transactions on Programming Languages and Systems

Parallel Computing and Optimization TechniquesLogic, programming, and type systems

Cited by 155

An experimental study of a virtual reality counselling paradigm using embodied self-dialogue

Slater, M., Neyret, S., Johnston, T., Iruretagoyena, G., Crespo, M. Á. D. L. C., Alabèrnia-Segura, M., Spanlang, B., & Feixas, G. (2019) · Scientific Reports

Virtual Reality Applications and ImpactsDigital Mental Health Interventions

Cited by 155

Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content

Lundgard, A., & Satyanarayan, A. (2022) · IEEE Transactions on Visualization and Computer Graphics

Data Visualization and AnalyticsDigital Accessibility for Disabilities

Cited by 155

Adaptive Context Network for Scene Parsing

Fu, J., Liu, J., Wang, Y., Li, Y., Bao, Y., Tang, J., & Lu, H. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsRemote-Sensing Image Classification

Cited by 155

A Framework for QoS-aware Traffic Classification Using Semi-supervised Machine Learning in SDNs

Wang, P., Lin, S.-C., & Luo, M. (2016) · 2016 IEEE International Conference on Services Computing (SCC)

Software-Defined Networks and 5GInternet Traffic Analysis and Secure E-voting

Cited by 155

Automation and Accountability in Decision Support System Interface Design

Cummings, M. L. (2006) · Journal of Technology Studies

Ethics and Social Impacts of AIInformation Systems Theories and Implementation

Cited by 155

Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut

Wang, Y., Shen, X., Hu, S. X., Yuan, Y., Crowley, J. L., & Vaufreydaz, D. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 155

A Practical-Time Related-Key Attack on the KASUMI Cryptosystem Used in GSM and 3G Telephony

Dunkelman, O., Keller, N., & Shamir, A. (2010) · Lecture Notes in Computer Science

Cryptographic Implementations and SecurityCoding theory and cryptography

Cited by 155

Spatial transcriptomics inferred from pathology whole-slide images links tumor heterogeneity to survival in breast and lung cancer

Levy-Jurgenson, A., Tekpli, X., Kristensen, V. N., & Yakhini, Z. (2020) · Scientific Reports

AI in cancer detectionSingle-cell and spatial transcriptomics

Cited by 155

Self-supervised learning for videos: A survey

Schiappa, M. C., Rawat, Y. S., & Shah, M. (2023) · ACM Computing Surveys

Domain Adaptation and Few-Shot LearningHuman Pose and Action Recognition

Cited by 155

PAL: Program-aided Language Models

Gao, L., Madaan, A., Zhou, S., Alon, U., Liu, P., Yang, Y., Callan, J., & Neubig, G. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 155

Comparison of discriminative input and output transformations for speaker adaptation in the hybrid NN/HMM systems

Li, B., & Sim, K. C. (2010) · Interspeech 2010

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 155

Audio-visual emotion fusion (AVEF): A deep efficient weighted approach

Ma, Y., Hao, Y., Chen, M., Chen, J., Lu, P., & Košir, A. (2019) · Information Fusion

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 155

Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study

Sui, Y., Zhou, M., Zhou, M., Han, S., & Zhang, D. (2024) · Proceedings of the 17th ACM International Conference on Web Search and Data Mining

Topic ModelingMultimodal Machine Learning Applications

Cited by 155

Multiple Instance Active Learning for Object Detection

Yuan, T., Wan, F., Fu, M., Liu, J., Xu, S., Ji, X., & Ye, Q. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Machine Learning and AlgorithmsAdvanced Neural Network Applications

Cited by 155

"I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models

Gadiraju, V., Kane, S., Dev, S., Taylor, A., Wang, D., Denton, R., & Brewer, R. (2023) · 2023 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIDisability Rights and Representation

Cited by 155

Fog Computing-Based IoT for Health Monitoring System

Paul, A., Pinjari, H., Hong, W.-H., Seo, H. C., & Rho, S. (2018) · Journal of Sensors

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 155

Domain General Face Forgery Detection by Learning to Weight

Sun, K., Liu, H., Ye, Q., Gao, Y., Liu, J., Shao, L., & Ji, R. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionFace recognition and analysis

Cited by 155

Modeling TTL-based Internet caches

Jung, J., Berger, A. W., & Balakrishnan, H. (2004) · IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428)

Caching and Content DeliveryNetwork Traffic and Congestion Control

Cited by 155

ProcTHOR: Large-Scale Embodied AI Using Procedural Generation

Deitke, M., VanderBilt, E., Herrasti, A., Weihs, L., Salvador, J., Ehsani, K., Han, W., Kolve, E., Farhadi, A., Kembhavi, A., et al. (2022) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 155

A medical multimodal large language model for future pandemics

Liu, F., Zhu, T., Wu, X., Yang, B., You, C., Wang, C., Lu, L., Liu, Z., Zheng, Y., Sun, X., et al. (2023) · npj Digital Medicine

Multimodal Machine Learning ApplicationsCOVID-19 diagnosis using AI

Cited by 155

16.3 A 23Mb/s 23pJ/b fully synthesized true-random-number generator in 28nm and 65nm CMOS

Yang, K., Fick, D., Henry, M. B., Lee, Y., Blaauw, D., & Sylvester, D. (2014) · 2014 IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC)

Physical Unclonable Functions (PUFs) and Hardware SecurityLow-power high-performance VLSI design

Cited by 155