Check computer science papers: citations, claims and retractions

Frequency-Aware Masked Autoencoders for Human Activity Recognition using Accelerometers

Lorenzen, N. R., Jennum, P. J., Mignot, E., & Brink-Kjaer, A. (2025) · 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 2

Annotation Sensitivity: Training Data Collection Methods Affect Model Performance

Kern, C., Eckman, S., Beck, J., Chew, R., Ma, B., & Kreuter, F. (2023) · arXiv

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 2

Does Functional Package Management Enable Reproducible Builds at Scale? Yes.

Malka, J., Zacchiroli, S., & Zimmermann, T. (2025) · 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR)

Software Engineering ResearchScientific Computing and Data Management

Cited by 2

Relative Navigation and Terrain-based Path Planning using Flash LiDAR based Surfel Grid Map for Asteroid Exploration

Liu, B., & Janschek, K. (2022) · IFAC-PapersOnLine

Robotics and Sensor-Based LocalizationReinforcement Learning in Robotics

Cited by 2

Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference

Tang, J., Zhao, Y., Zhu, K., Xiao, G., Kasikci, B., & Han, S. (2024) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 2

Are Retrials All You Need? Enhancing Large Language Model Reasoning Without Verbalized Feedback

Potamitis, N., & Arora, A. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Models

Zhang, Y., Du, L., Cao, D., Fu, Q., & Liu, Y. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Self-Training Meets Consistency: Improving LLMs’ Reasoning with Consistency-Driven Rationale Evaluation

Lee, J., Sakaguchi, K., & Bak, J. (2025) · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 2

A pre-trained language model approach for triaging surgical patients for preoperative anesthesia clinics

Xu, N. Y., Litake, O., Tully, J. L., Meineke, M. N., Sinha, A., Meyer, M., & Gabriel, R. A. (2025) · Journal of Clinical Monitoring and Computing

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 2

iThelma: An Autonomous LLM Agent for Cyber Threat Hunting via Playbook-Driven Intelligence

Chen, N., Lin, R., Xie, D., Lin, H., & Chen, S. (2025) · 2025 IEEE Conference on Communications and Network Security (CNS)

Network Security and Intrusion DetectionDigital and Cyber Forensics

Cited by 2

From English-Centric to Effective Bilingual: LLMs with Custom Tokenizers for Underrepresented Languages

Kiulian, A., Polishko, A., Khandoga, M., Kostiuk, Y., Gabrielli, G., Gagała, Ł., Zaraket, F., Abu Obaida, Q., Garud, H., Wing Yee Mak, W., et al. (2025) · Proceedings of the Fourth Ukrainian Natural Language Processing Workshop (UNLP 2025)

Natural Language Processing TechniquesTopic Modeling

Cited by 2

Cross-Lingual Multi-Hop Knowledge Editing

Khandelwal, A., Singh, H., Gu, H., Chen, T., & Zhou, K. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

BrowseComp-Plus: A Fair and Disentangled Evaluation Benchmark for Deep Search Agents

Chen, Z., Ma, X., Zhuang, S., Nie, P., Zou, K., Sharifymoghaddam, S., Liu, A., Green, J., Patel, K., Meng, R., et al. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Information Retrieval and Search BehaviorTopic Modeling

Cited by 2

HyperAgent: Generalist Software Engineering Agents to Solve Coding Tasks at Scale

Phan, H. N., Nguyen, T. N., Nguyen, P. X., & Bui, N. D. Q. (2024) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 2

Accelerating Multimodal Large Language Models via Dynamic Visual-Token Exit and the Empirical Findings

Wu, Q., Lin, W., Zhou, Y., Ye, W., Zen, Z., Sun, X., & Ji, R. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 2

Trust Between AI Agents: Measuring Formation, Breakage, and Recovery, with Implications for Governing Multi-Agent Systems

Chen, Y. (2026) · arXiv

Access Control and TrustEthics and Social Impacts of AI

Cited by 2

A systematic evaluation of explainable AI methods for high-dimensional transcriptome-based cancer survival prediction

Zuo, Y., Yang, S., & Zhao, W. (2026) · Frontiers in Physiology

Explainable Artificial Intelligence (XAI)Gene expression and cancer classification

Cited by 2

Noveltybench: Evaluating language models for humanlike diversity

Zhang, Y., Diddee, H., Holm, S., Liu, H., Liu, X., Samuel, V., Wang, B., & Ippolito, D. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

INMS: Memory Sharing for Large Language Model based Agents

Gao, H., & Zhang, Y. (2024) · arXiv

Speech and dialogue systemsMulti-Agent Systems and Negotiation

Cited by 2

Joint Client Scheduling and Resource Allocation Under Channel Uncertainty in Federated Learning

Wadu, M. M., Samarakoon, S., & Bennis, M. (2021) · IEEE Transactions on Communications

Privacy-Preserving Technologies in DataAdvanced Wireless Network Optimization

Cited by 2

Inductive Learning of Logical Theories with LLMs: A Expressivity-graded Analysis

De Souza, J. P. G., Carvalho, D., & Freitas, A. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence

Logic, Reasoning, and KnowledgeNatural Language Processing Techniques

Cited by 2

Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Subramaniam, V., Du, Y., Tenenbaum, J. B., Torralba, A., Li, S., & Mordatch, I. (2025) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 2

No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery

Rutherford, A., Beukman, M., Willi, T., Lacerda, B., Hawes, N., & Foerster, J. (2024) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 2

Evolving Deeper LLM Thinking

Lee, K.-H., Fischer, I., Wu, Y.-H., Marwood, D., Baluja, S., Schuurmans, D., & Chen, X. (2025) · arXiv

Topic ModelingAI-based Problem Solving and Planning

Cited by 2