Check computer science papers: citations, claims and retractions

Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation

Chen, X., Chen, Z., Li, J., Zhang, Y.-D., Lin, X., & Qian, X. (2022) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesAI in cancer detection

Cited by 34

Measuring Attribution in Natural Language Generation Models

Rashkin, H., Nikolaev, V., Lamm, M., Aroyo, L., Collins, M., Das, D., Petrov, S., Tomar, G. S., Turc, I., & Reitter, D. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 34

Applying Machine Learning for Sensor Data Analysis in Interactive Systems: Common Pitfalls of Pragmatic Use and Ways to Avoid Them

PlÖtz, T. (2022) · ACM Computing Surveys

Context-Aware Activity Recognition SystemsData Visualization and Analytics

Cited by 34

Ensemble Method for Sexual Predators Identification in Online Chats

Fauzi, M. A., & Bours, P. (2020) · 2020 8th International Workshop on Biometrics and Forensics (IWBF)

Hate Speech and Cyberbullying DetectionText and Document Classification Technologies

Cited by 34

Robust Text Classification in the Presence of Confounding Bias

Landeiro, V., & Culotta, A. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence

Text and Document Classification TechnologiesAdvanced Causal Inference Techniques

Cited by 34

CounterFAccTual: How FAccT Undermines Its Organizing Principles

Gansky, B., & McDonald, S. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 34

Language models are not naysayers: an analysis of language models on negation benchmarks

Truong, T. H., Baldwin, T., Verspoor, K., & Cohn, T. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 34

How UX Practitioners Produce Findings in Usability Testing

Reeves, S. (2019) · ACM Transactions on Computer-Human Interaction

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 34

Evaluating LLMs on document-based QA: Exact answer selection and numerical extraction using CogTale dataset

Rasool, Z., Kurniawan, S., Balugo, S., Barnett, S., Vasa, R., Chesser, C., Hampstead, B. M., Belleville, S., Mouzakis, K., & Bahar-Fuchs, A. (2024) · Natural Language Processing Journal

Topic ModelingInformation Retrieval and Search Behavior

Cited by 34

The truth is hard to make: Validation of medical image registration

Pluim, J. P. W., Muenzing, S. E. A., Eppenhof, K. A. J., & Murphy, K. (2016) · 2016 23rd International Conference on Pattern Recognition (ICPR)

Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques

Cited by 34

Explicit State Duration HMM for Abnormality Detection in Sequences of Human Activity

Lühr, S., Venkatesh, S., West, G., & Bui, H. H. (2004) · Lecture Notes in Computer Science

Context-Aware Activity Recognition SystemsAnomaly Detection Techniques and Applications

Cited by 34

A Preliminary Investigation on Horses Recognition Using Facial Texture Features

Jarraya, I., Ouarda, W., & Alimi, A. M. (2015) · 2015 IEEE International Conference on Systems, Man, and Cybernetics

Face and Expression RecognitionFace recognition and analysis

Cited by 34

Video ReCap: Recursive Captioning of Hour-Long Videos

Islam, M. M., Ho, N., Yang, X., Nagarajan, T., Torresani, L., & Bertasius, G. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsVideo Analysis and Summarization

Cited by 34

Learning Through Exploration: How Children, Adults, and Older Adults Interact with a New Feature-Rich Application

Mahmud, S., Alvina, J., Chilana, P. K., Bunt, A., & McGrenere, J. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignTechnology Use by Older Adults

Cited by 34

A General Framework for Information Extraction using Dynamic Span Graphs

Luan, Y., Wadden, D., He, L., Shah, A., Ostendorf, M., & Hajishirzi, H. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 34

Introduction to Explainable AI

Liao, Q. V., Singh, M., Zhang, Y., & Bellamy, R. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 34

Probabilistic Graphical Models for Boosting Cardinal and Ordinal Peer Grading in MOOCs

Mi, F., & Yeung, D.-Y. (2015) · Proceedings of the AAAI Conference on Artificial Intelligence

Online Learning and AnalyticsStudent Assessment and Feedback

Cited by 34

Detecting Alzheimer’s Disease from Speech Using Neural Networks with Bottleneck Features and Data Augmentation

Liu, Z., Guo, Z., Ling, Z., & Li, Y. (2021) · ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisDementia and Cognitive Impairment Research

Cited by 34

Chaos-Based Encryption for Digital Images and Videos

Li, S., Chen, G., & Zheng, X. (2004) · Multimedia Security Handbook

Chaos-based Image/Signal EncryptionAdvanced Steganography and Watermarking Techniques

Cited by 34

The Feel of Algorithms

Ruckenstein, M. (2023) · University of California Press eBooks

Ethics and Social Impacts of AICybernetics and Technology in Society

Cited by 34

Collaborative localization with heterogeneous inter-robot measurements by Riemannian optimization

Knuth, J., & Barooah, P. (2013) · 2013 IEEE International Conference on Robotics and Automation

Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks

Cited by 34

FingerText: Exploring and Optimizing Performance for Wearable, Mobile and One-Handed Typing

Lee, D., Kim, J., & Oakley, I. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Interactive and Immersive DisplaysUsability and User Interface Design

Cited by 34

Memory Dynamics in Attractor Networks with Saliency Weights

Tang, H., Li, H., & Yan, R. (2010) · Neural Computation

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 34

Measuring Progress on Scalable Oversight for Large Language Models

Bowman, S. R., Hyun, J., Perez, E., Chen, E., Pettit, C., Heiner, S., Lukošiūtė, K., Askell, A., Jones, A., Chen, A., et al. (2022) · arXiv

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 34