Check computer science papers: citations, claims and retractions

SWE-ABS: Adversarial Benchmark Strengthening Exposes Inflated Success Rates on Test-based Benchmark

Yu, B., Cao, Y., Zhang, Y., Lin, L., Xu, J., Zhong, Z., Xu, Q., Wang, G., Cao, J., Cheung, S.-C., et al. (2026) · arXiv

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 2

Unified approach to data-driven quantum error mitigation

Lowe, A., Gordon, M. H., Czarnik, P., Arrasmith, A., Coles, P. J., & Cincio, L. (2020) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 2

Transformers, parallel computation, and logarithmic depth

Sanford, C., Hsu, D., & Telgarsky, M. (2024) · arXiv

Neural Networks and ApplicationsParallel Computing and Optimization Techniques

Cited by 2

Federated learning for cognitive impairment detection using speech data

Blazquez-Folch, J., Limones Andrade, M., Calm, B., Auñón García, J. M., Alegret, M., Muñoz, N., Cano, A., Fernández, V., García-Gutiérrez, F., De Rojas, I., et al. (2025) · Frontiers in Artificial Intelligence

Privacy-Preserving Technologies in DataDementia and Cognitive Impairment Research

Cited by 2

Insider Threat Identification From Accessed Website Content Optimized by Modified Metaheuristic

Jovanovic, L., Kaljevic, J., Zivkovic, M., Bacanin, N., Antonijevic, M., & Cajic, M. (2024) · 2024 International Conference on Circuit, Systems and Communication (ICCSC)

Information and Cyber SecurityNetwork Security and Intrusion Detection

Cited by 2

Proceedings of the 2nd workshop on Emotion Representations and Modelling for Companion Systems

(2016)

Intelligent Tutoring Systems and Adaptive LearningEmotion and Mood Recognition

Cited by 2

Light-weight probing of unsupervised representations for reinforcement learning

Zhang, W., GX-Chen, A., Sobal, V., LeCun, Y., & Carion, N. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 2

Relating Children’s Automatically Detected Facial Expressions to Their Behavior in RoboTutor

Saxena, M., Pillai, R., & Mostow, J. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Intelligent Tutoring Systems and Adaptive LearningSocial Robot Interaction and HRI

Cited by 2

Hydragen: High-Throughput LLM Inference with Shared Prefixes

Juravsky, J., Brown, B., Ehrlich, R., Fu, D. Y., Ré, C., & Mirhoseini, A. (2024) · arXiv

Parallel Computing and Optimization TechniquesTopic Modeling

Cited by 2

Stochastic parrots looking for stochastic parrots: LLMs are easy to fine-tune and hard to detect with other LLMs

Henrique, D. S. G., Kucharavy, A., & Guerraoui, R. (2023) · arXiv

Adversarial Robustness in Machine LearningAuthorship Attribution and Profiling

Cited by 2

Artificial Intelligence Risk Identification: Challenges, Impacts, and Mitigation Strategies

Syukrina, U., & Nugraha, I. G. D. (2025) · International Journal of Electrical, Computer, and Biomedical Engineering

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2

Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

Hägele, A., Bakouch, E., Kosson, A., Allal, L. B., Von Werra, L., & Jaggi, M. (2024) · arXiv

Stochastic Gradient Optimization TechniquesMachine Learning and Data Classification

Cited by 2

Task-Specific Zero-Shot Quantization-Aware Training for Object Detection

Li, C., Chen, X., Wang, J., Zhao, K., & Chen, J. (2025) · 2025 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2

A biologically inspired architecture with switching units can learn to generalize across backgrounds

Voina, D., Shea-Brown, E., & Mihalas, S. (2023) · Neural Networks

Domain Adaptation and Few-Shot LearningNeural Networks and Applications

Cited by 2

Building models, building capacity: A review of participatory machine learning for HIV prevention

Sendak, M., Young, M., Kim, J. Y., Hasan, A., Kelsey, C., O’Neal, C., Jagneaux, T., Wilbright, W., Couk, J., Lim, S., et al. (2025) · PLOS Global Public Health

Ethics and Social Impacts of AIHIV/AIDS Research and Interventions

Cited by 2

What Makes a Reward Model a Good Teacher? An Optimization Perspective

Razin, N., Wang, Z., Strauss, H., Wei, S., Lee, J. D., & Arora, S. (2025) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 2

Designing towards productivity: A centralized ai assistant concept for work

Cao, T., Qing Khoo, Y., Birajdar, S., Gong, Z., Chung, C.-F., Moghaddam, Y., Xu, A., Mehta, H., Shukla, A., Wang, Z., et al. (2024) · AHFE International

Usability and User Interface DesignAI in Service Interactions

Cited by 2

Counting collisions in random circuit sampling for benchmarking quantum computers

Mari, A. (2024) · APL Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 2

Prediction-based outlier detection with explanations

Chen, L.-C., Kuo, T.-T., Lai, W.-C., Lin, S.-D., & Tsai, C.-H. (2012) · 2012 IEEE International Conference on Granular Computing

Anomaly Detection Techniques and ApplicationsAdvanced Statistical Methods and Models

Cited by 2

Towards Explainable and Trustworthy Autonomous Physical Systems

Omeiza, D., Anjomshoae, S., Kollnig, K., Camburu, O.-M., Främling, K., & Kunze, L. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Safety Systems Engineering in Autonomy

Cited by 2

Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models

Qiu, Y., Embar, V., Zhang, Y., Jaitly, N., Cohen, S. B., & Han, B. (2025) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 2

Measuring Free-Form Decision-Making Inconsistency of Language Models in Military Crisis Simulations

Shrivastava, A., Hullman, J., & Lamparth, M. (2024) · arXiv

Topic ModelingEthics and Social Impacts of AI

Cited by 2

Are numerical or verbal explanations of AI the key to appropriate user reliance and error detection?

Papenkordt, J., Ngonga Ngomo, A.-C., & Thommes, K. (2026) · Behaviour & Information Technology

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

Cited by 2

Quantum Deformed Neural Networks

Bondesan, R., & Welling, M. (2020) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 2