Check computer science papers: citations, claims and retractions

High accuracy design and realization of fixed and variable allpass-based fractional delay digital filters

Stoyanov, G. K., Nikolova, K. S., & Markova, V. I. (2009) · 2009 9th International Conference on Telecommunication in Modern Satellite, Cable, and Broadcasting Services

Digital Filter Design and ImplementationAnalog and Mixed-Signal Circuit Design

Cited by 1

Physically plausible data augmentations in contrastive learning for wearable IMU-based activity recognition

Oishi, N., Birch, P., Lago, P., & Roggen, D. (2026) · Knowledge-Based Systems

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 1

Multi-LLM Collaborative Search for Complex Problem Solving

Yang, S., Li, Y., Lam, W., & Cheng, Y. (2025) · arXiv

Topic ModelingAI-based Problem Solving and Planning

Cited by 1

FISMI-DRL: A Framework for Interactive Segmentation of Medical Image Based On Deep Reinforcement Learning

Qian, C., Yang, H., & Li, J. (2023) · 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1

NeuroMAC НЕЙРОСЕТЕВОЙ КОД АУТЕНТИФИКАЦИИ СООБЩЕНИЙ С ПАКЕТНЫМ УСКОРЕНИЕМ 174×, ПОЛНЫМ ПРОХОЖДЕНИЕМ NIST SP 800-22 (15/15) И УСТОЙЧИВОСТЬЮ К TIMING ATTACKS

Суркова, М. (2026)

Cryptographic Implementations and SecurityCoding theory and cryptography

Cited by 1

From technology to activity development: the challenge of using students as participants in a PD project

Molin-Juustila, T., Kuutti, K., Nuojua, J., Soudunsaari, L., Juustila, A., & Hentilä, H.-L. (2014) · Proceedings of the 13th Participatory Design Conference on Research Papers - PDC '14

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 1

The Effect of Explainable AI-based Decision Support on Human Task Performance: A Meta-Analysis

Haag, F. (2025) · arXiv

Explainable Artificial Intelligence (XAI)Human-Automation Interaction and Safety

Cited by 1

Dissecting Language Models: Machine Unlearning via Selective Pruning

Pochinkov, N., & Schoots, N. (2024) · arXiv

Privacy-Preserving Technologies in DataAdvanced Neural Network Applications

Cited by 1

Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data

Tamber, M. S., Kazi, S., Sourabh, V., & Lin, J. (2025) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 1

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions

Hu, Y., Wang, Y., & McAuley, J. (2025) · arXiv

Topic ModelingAI-based Problem Solving and Planning

Cited by 1

LLF-Bench: Benchmark for Interactive Learning from Language Feedback

Cheng, C.-A., Kolobov, A., Misra, D., Nie, A., & Swaminathan, A. (2023) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 1

Oracle Autonomous Database for Transforming Database Administration by Harnessing Artificial Intelligence

Avula, S. B. (2025) · 2025 Global Conference in Emerging Technology (GINOTECH)

Advanced Database Systems and QueriesCloud Computing and Resource Management

Cited by 1

AgentMemBench: A Systematic Benchmark for Evaluating Long-Term Memory Management Strategies in Conversational AI Agents

Cherif, A. (2026) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 1

S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models

Dai, M., Yang, C., & Si, Q. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Psychologically Enhanced AI Agents

Besta, M., Chandran, S., Gerstenberger, R., Lindner, M., Chrapek, M., Martschat, S. H., Ghandi, T., Iff, P., Niewiadomski, H., Nyczyk, P., et al. (2025) · arXiv

Psychiatry, Mental Health, NeuroscienceSpeech and dialogue systems

Cited by 1

Reasoning with Exploration: An Entropy Perspective

Cheng, D., Huang, S., Zhu, X., Dai, B., Zhao, W. X., Zhang, Z., & Wei, F. (2025) · arXiv

Reinforcement Learning in RoboticsTopic Modeling

Cited by 1

Mini Minds: Exploring Bebeshka and Zlata Baby Models

Proskurina, I., Metzler, G., & Velcin, J. (2023) · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning

Topic ModelingNatural Language Processing Techniques

Cited by 1

The Red Queen Gödel Machine: Co-Evolving Agents and Their Evaluators

Iacob, A., Jovanović, A., Shen, W. F., Burkhardt, D., Kurmanji, M., Tastan, N., Sani, L., Venanzi, N. A. E., Nie, J., Odonnat, A., et al. (2026) · arXiv

Evolutionary Algorithms and ApplicationsSoftware Engineering Research

Cited by 1

Lightweight Identification of Malicious IoT Traffic via Cross-View Knowledge Distillation

Nie, F., Liu, W., Liu, G., Gao, B., Huang, J., & Yuen, C. (2025) · IEEE Internet of Things Journal

Network Security and Intrusion DetectionInternet Traffic Analysis and Secure E-voting

Cited by 1

Augmented reality in exposure therapy assistance: A clinical point of view

Rodrigues, J. A., Merlin, B., & Fülber, H. (2023) · METHODOLOGY FOCUSED ON THE AREA OF INTERDISCIPLINARITY- V1

Augmented Reality ApplicationsVirtual Reality Applications and Impacts

Cited by 1

Automated Data Quality Control System in Health and Demographic Surveillance System

Tlouyamma, J., & Mokwena, S. (2024) · Science, Engineering and Technology

Data Quality and ManagementElectronic Health Records Systems

Cited by 1

How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Deng, Y., Song, Z., Xiong, J., & Yang, C. (2024) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1

xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations

Chen, K., Ren, Y., Liu, Y., Hu, X., Tian, H., Xie, T., Liu, F., Zhang, H., Liu, H., Gong, Y., et al. (2025) · arXiv

Artificial Intelligence ApplicationsAI and HR Technologies

Cited by 1

Neural networks for step edge detection

Liao, F.-Y., Middler, M., & Lin, W.-C. (2002) · IJCNN-91-Seattle International Joint Conference on Neural Networks

Image and Object Detection TechniquesAdvanced Neural Network Applications

Cited by 1