Check computer science papers: citations, claims and retractions

Data Observability and Self-Healing Pipeline Architecture in Regulated Enterprises: Proactive Anomaly Detection, Schema Drift Management, and Automated Recovery Strategies

Reddy Gaddam, S. (2024) · International Journal of Computational and Experimental Science and Engineering

Software System Performance and ReliabilityData Quality and Management

Cited by 0

Influenced Encryption Key for AES based MF-TDMA in Mobile Communication

Ho Jeong, W., Ju, S.-L., Cho, J.-P., & Kim, K.-S. (2026) · International Journal of Engineering and Technology

Cryptographic Implementations and SecurityChaos-based Image/Signal Encryption

Cited by 0

Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction

Bui, N., Nguyen, H. T., Cohan, A., & Ying, R. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Five Queries Are Enough: Query-Efficient and Surrogate-Free Membership Inference Attacks on RAG via Entailment

Nguyen, N. L. B., Ma, W., Vo, V., Abuadbba, A., Fang, M., Zhang, J., & Xiang, Y. (2026) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 0

Cache What Lasts: Token Retention for Memory-Bounded KV Cache in LLMs

Bui, N., Sharma, S., Lamba, S., Mishra, S., & Ying, R. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Reason Popper-ly: Patching In-Context Reasoning with Inductive Logic Programming

Chen, Z., & Ma, M. (2026) · arXiv

Logic, Reasoning, and KnowledgeTopic Modeling

Cited by 0

LLM-Assisted Empirical Software Engineering: Systematic Literature Review and Research Agenda

Gomes, V., Selb, D., Palomba, F., Spinola, R., & Lo, D. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

Test coverage for network configurations

Xu, X., Deng, W., Beckett, R., Mahajan, R., & Walker, D. (2022) · arXiv

Software Testing and Debugging TechniquesSoftware-Defined Networks and 5G

Cited by 0

LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Li, D., Cao, S., Griggs, T., Liu, S., Mo, X., Tang, E., Hegde, S., Hakhamaneshi, K., Patil, S. G., Zaharia, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

A-Evolve-Training: Autonomous Post-Training of a 30B Model

Shi, Z., He, B., Sang, Y., Dumoulin, B., & Lu, H. (2026) · arXiv

Artificial Intelligence ApplicationsTopic Modeling

Cited by 0

LocAgent: Graph-Guided LLM Agents for Code Localization

Chen, Z., Tang, X., Deng, G., Wu, F., Wu, J., Jiang, Z., Prasanna, V., Cohan, A., & Wang, X. (2025) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 0

G-Long: Graph-Enhanced Memory Management for Efficient Long-Term Dialogue Agents

Choi, M., Jang, Y., Youn, S., & Ko, Y. (2026) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 0

Context as Infrastructure: Knowledge Compilation for Retrieval in Agentic Systems with Harnesses

Yu, Z., Cao, B., Idriss, S., Wang, Q., Xu, G., Qin, L., Jin, X., Liu, A., Cai, S., Bao, X., et al. (2026) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 0

Linear Attention Sequence Parallelism

Sun, W., Qin, Z., Li, D., Shen, X., Qiao, Y., & Zhong, Y. (2024) · arXiv

Parallel Computing and Optimization TechniquesTopic Modeling

Cited by 0

PIPPA: A Partially Synthetic Conversational Dataset

Gosling, T., Dale, A., & Zheng, Y. (2023) · arXiv

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 0

MobileCLIP2: Improving Multi-Modal Reinforced Training

Faghri, F., Vasu, P. K. A., Koc, C., Shankar, V., Toshev, A., Tuzel, O., & Pouransari, H. (2025) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 0

Learning Hierarchical Procedural Memory for LLM Agents through Bayesian Selection and Contrastive Refinement

Forouzandeh, S., Peng, W., Moradi, P., Yu, X., & Jalili, M. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Exact-Solution Volume and Length Generalization in Transformers

Zhu, Y. J., & Chiang, D. (2026) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 0

Leveraging Sequentiality in Reinforcement Learning from a Single Demonstration

Chenu, A., Serris, O., Sigaud, O., & Perrin-Gilbert, N. (2022) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 0

MAPLE-Guard: Memory-Aware Link Enforcement Against Memory-Link Poisoning in Multi-Agent Systems

Xiong, W., Zhou, Y., Wang, J., Gu, S., Tang, B., Li, Z., Xiong, F., Wen, Y., & Wen, M. (2026) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 0

Assessing Awareness and Usage of AI Tools Among Faculty and Learners in Higher Education Institutions in Sub‑Saharan Africa

Soko, J., Pete, J., & Mureithi, G. (2025) · Asian Journal of Distance Education

Artificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

Cited by 0

Learning Technologies and Learning Resources in Computing Science Higher Education: Exploring Access, Adoption, and Effectiveness in relation to Regional Context

Paterson, J., Oyelere, S. S., Dubay, C., & Izu, C. (2025) · Working Group Reports of the ACM Global Computing Education Conference 2025

Open Education and E-LearningEducational Technology and E-Learning

Cited by 0

Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning

Jin, C., Peng, H., Zhang, Q., Zhou, Y., Tang, Y., Che, T., & Metaxas, D. N. (2025) · arXiv

Topic ModelingMulti-Agent Systems and Negotiation

Cited by 0

Self-Evolving Deep Research via Joint Generation and Evaluation

Zhu, H., Cai, C., Song, Y., Chen, X., Han, S., & Guo, Y. (2026) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0