Check computer science papers: citations, claims and retractions

Automatic Discovery of Privacy–Utility Pareto Fronts

Avent, B., González, J., Diethe, T., Paleyes, A., & Balle, B. (2020) · Proceedings on Privacy Enhancing Technologies

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 3

Towards secondary structure prediction of longer mRNA sequences using a quantum-centric optimization scheme

Kumar, V., Alevras, D., Metkar, M., Welling, E., Cade, C., Niesen, I., Friedhoff, T., Park, J.-E., Shivpuje, S., LaDue, M., et al. (2025) · arXiv

Quantum Computing Algorithms and ArchitectureRNA and protein synthesis mechanisms

Cited by 3

Environmental sound classification using log-Gabor filter

Souli, S., & Lachiri, Z. (2012) · 2012 IEEE 11th International Conference on Signal Processing

Music and Audio ProcessingSpeech Recognition and Synthesis

Cited by 3

LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation

Han, D., Couturier, C., Madrigal Diaz, D., Zhang, X., Rühle, V., & Rajmohan, S. (2026) · Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems

AI-based Problem Solving and PlanningMulti-Agent Systems and Negotiation

Cited by 3

Variational probabilistic fusion network for RGB-T semantic segmentation

Lin, B., Lin, Z., Guo, Y., Zhang, Y., Zou, J., & Fan, S. (2023) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 3

Multi-Modal generative AI systems: Bridging text, vision and speech with advanced LLM Architectures

John, D. (2023) · International Journal of Science and Research Archive

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 3

Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization

Wan, X., Sun, R., Nakhost, H., & Arik, S. (2024) · Advances in Neural Information Processing Systems 37

Natural Language Processing TechniquesTopic Modeling

Cited by 3

A Temporal Extension of Latent Dirichlet Allocation for Unsupervised Acoustic Unit Discovery

van der Merwe, W., Kamper, H., & Adam du Preez, J. (2022) · Interspeech 2022

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 3

When Retrieval Augmentation Meets API Documentation: Can LLMs Code with Less-Common Libraries?

Chen, J., Chen, S., Cao, J., Shen, J., & Cheung, S.-C. (2026) · ACM Transactions on Software Engineering and Methodology

Software Engineering ResearchTopic Modeling

Cited by 3

Wireless Image Retrieval at the Edge

Jankowski, M., Gunduz, D., & Mikolajczyk, K. (2021) · IEEE Journal on Selected Areas in Communications

Advanced Data Compression TechniquesIoT and Edge/Fog Computing

Cited by 3

Open Source Software Development as Gift Culture: Work and Identity Formation in an Internet Community

Bergquist, M. (2020) · New Technologies at Work

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 3

Application Model of Video Surveillance System Interworking Based on Blockchain

Li, J., Liu, X., Zhao, J., Liang, W., & Guo, L. (2021) · 2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 3

Remarks on Bounds for Quantum Codes

Ashikhmin, A. (1997) · arXiv

Quantum Computing Algorithms and ArchitectureCoding theory and cryptography

Cited by 3

Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Models

Castillo-Bolado, D., Davidson, J., Gray, F., & Rosa, M. (2024) · Advances in Neural Information Processing Systems 37

Topic ModelingSpeech and dialogue systems

Cited by 3

AIOpsLab: a holistic framework to evaluate AI agents for enabling autonomous clouds

Chen, Y., Shetty, M., Somashekar, G., Ma, M., Simmhan, Y., Mace, J., Bansal, C., Wang, R., & Rajmohan, S. (2025) · arXiv

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 3

AI-Driven Usability Testing: Integrating Eye-Tracking Data and Agentic Systems for Automated UI Evaluation

Kadegaonkar, M., & Karim, K. (2025) · Proceedings of the AAAI Symposium Series

Usability and User Interface DesignGaze Tracking and Assistive Technology

Cited by 3

Progent: Securing AI Agents with Privilege Control

Shi, T., He, J., Wang, Z., Li, H., Wu, L., Guo, W., & Song, D. (2025) · arXiv

Security and Verification in ComputingAdversarial Robustness in Machine Learning

Cited by 3

Cyber Defense through Agentic AI Enabled Automation: An Approach to Reduce Cyber Risk

Vajpayee, P., & Hossain, G. (2025) · Proceedings of the 2025 Computers and People Research Conference

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 3

Threshold for Fault-tolerant Quantum Advantage with the Quantum Approximate Optimization Algorithm

Omanakuttan, S., He, Z., Zhang, Z., Hao, T., Babakhani, A., Boulebnane, S., Chakrabarti, S., Herman, D., Sullivan, J., Perlin, M. A., et al. (2025) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 3

AnimaX: Animating the Inanimate in 3D with Joint Video-Pose Diffusion Models

Huang, Z., Feng, H., Sun, Y.-T., Guo, Y.-C., Cao, Y.-P., & Sheng, L. (2025) · Proceedings of the SIGGRAPH Asia 2025 Conference Papers

Human Motion and Animation3D Shape Modeling and Analysis

Cited by 3

How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior

Xiong, Z., Lin, Y., Xie, W., He, P., Liu, Z., Tang, J., Lakkaraju, H., & Xiang, Z. (2025) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 3

LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation

Han, D., Couturier, C., Diaz, D. M., Zhang, X., Rühle, V., & Rajmohan, S. (2025) · arXiv

AI-based Problem Solving and PlanningMulti-Agent Systems and Negotiation

Cited by 3

Block Contextual MDPs for Continual Learning

Sodhani, S., Meier, F., Pineau, J., & Zhang, A. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 3

‘We can see a savage’: a case study of the colonial gaze in generative AI algorithms

Alenichev, A., Shaffer, J. D., Kingori, P., Grietens, K. P., Muldoon, J., & Rocher, L. (2026) · AI & SOCIETY

Ethics and Social Impacts of AICultural Studies and Colonialism

Cited by 3