Check computer science papers: citations, claims and retractions

Glob-Diffusion: A Global Consistent Diffusion Model for Large-Scale Image Generation

Kang, Y., Shi, H., Liu, H., Xie, W., Fang, L., & Bruzzone, L. (2026) · IEEE Transactions on Circuits and Systems for Video Technology

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 1

Explicit Memory Learning with Expectation Maximization

Yin, Z., Sun, Q., Guo, Q., Zeng, Z., Cheng, Q., Qiu, X., & Huang, X. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 1

TT-SI: Self-Improving LLM Agents with Test-Time Training

Acikgoz, E. C., Qian, C., Ji, H., Hakkani-Tür, D., & Tur, G. (2026) · Findings of the Association for Computational Linguistics: ACL 2026

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 1

In-Context LoRA for Diffusion Transformers

Huang, L., Wang, W., Wu, Z.-F., Shi, Y., Dou, H., Liang, C., Feng, Y., Liu, Y., & Zhou, J. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1

AI-Enhanced Anomaly Detection and Automated Root-Cause Analysis for Enterprise Data Platforms

Matla, R. K. (2026) · 2026 5th International Conference on Sentiment Analysis and Deep Learning (ICSADL)

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 1

APEX-MEM: Agentic Semi-Structured Memory with Temporal Reasoning for Long-Term Conversational AI

Banerjee, P., Moshtaghi, M., Subramanian, S., Misra, A., & Chadha, A. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Speech and dialogue systemsAI-based Problem Solving and Planning

Cited by 1

Impact of Retake Policy on Student Performance in a CS0 Course with Mastery Learning

Vambenepe, E., Pan, K., Kothari, A., Galler, A., Bernard, C. R., & Garcia, D. (2025) · Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 2

Teaching and Learning ProgrammingStudent Assessment and Feedback

Cited by 1

SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers

Xiang, Y., Yan, H., Ouyang, S., Gui, L., & He, Y. (2025) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 1

Falling and failing (to learn): Evidence from a nation-wide cybersecurity field experiment with SMEs

Gonzalez-Jimenez, D., Capozza, F., Dirkmaat, T., van de Veer, E., van Druten, A., & Baillon, A. (2025) · Journal of Economic Behavior & Organization

Spam and Phishing DetectionInformation and Cyber Security

Cited by 1

AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies

Zeng, Y., Yang, Y., Zhou, A., Tan, J. Z., Tu, Y., Mai, Y., Klyman, K., Pan, M., Jia, R., Song, D., et al. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 1

Quantize YOLOv3-tiny For 5-bit Hardware

Hua, Y., Yu, L., Meng, X., & Qin, Z. (2021) · 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1

OpenThoughts: Data Recipes for Reasoning Models

Guha, E., Marten, R., Keh, S., Raoof, N., Smyrnis, G., Bansal, H., Nezhurina, M., Mercat, J., Vu, T., Sprague, Z., et al. (2025) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 1

Edit at your own risk: evaluating the robustness of edited models to distribution shifts

Brown, D., Godfrey, C., Nizinski, C., Tu, J., & Kvinge, H. (2023) · arXiv

Adversarial Robustness in Machine LearningExplainable Artificial Intelligence (XAI)

Cited by 1

Dissecting Adversarial Robustness of Multimodal LM Agents

Wu, C. H., Shah, R., Koh, J. Y., Salakhutdinov, R., Fried, D., & Raghunathan, A. (2024) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1

Evaluating the Diversity and Quality of LLM Generated Content

Shypula, A., Li, S., Zhang, B., Padmakumar, V., Yin, K., & Bastani, O. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Correcting Biased Centered Kernel Alignment Measures in Biological and Artificial Neural Networks

Murphy, A., Zylberberg, J., & Fyshe, A. (2024) · arXiv

Neural Networks and ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1

A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Lee, K.-H., Chen, X., Furuta, H., Canny, J., & Fischer, I. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 1

Can Large Language Model Detect Plagiarism in Source Code?

Brach, W., Košt’ál, K., & Ries, M. (2024) · 2024 2nd International Conference on Foundation and Large Language Models (FLLM)

Software Engineering ResearchAcademic integrity and plagiarism

Cited by 1

O-Edit: Orthogonal Subspace Editing for Language Model Sequential Editing

Cai, Y., & Cao, D. (2024) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1

E-GEO: A Testbed for Generative Engine Optimization in E-Commerce

Bagga, P. S., Farias, V. F., Korkotashvili, T., Peng, T., & Wu, Y. (2025) · arXiv

Information Retrieval and Search BehaviorDigital Marketing and Social Media

Cited by 1

Solving Context Window Overflow in AI Agents

Labate, A. B., de Sousa, V. M., Fiorini, S. R., Azevedo, L. G., Thiago, R. M., & da Silva, V. T. (2025) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 1

Realgeneral: Unifying Visual Generation Via Temporal in-Context Learning With Video Models

Lin, Y., Huang, M., Zhuang, S., & Mao, Z. (2025) · 2025 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1

Edge–Cloud Collaboration for Machine Condition Monitoring: A Comprehensive Review of Mechanisms, Models, and Applications

Yu, L., Fang, J., Wang, Q., Li, F., & Liu, H. (2026) · Machines

IoT and Edge/Fog ComputingDigital Transformation in Industry

Cited by 1

Harnessing GANs for Zero-Shot Learning of New Classes in Visual Speech Recognition

Kumar, Y., Sahrawat, D., Maheshwari, S., Mahata, D., Stent, A., Yin, Y., Ratn Shah, R., & Zimmermann, R. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Speech and Audio ProcessingDomain Adaptation and Few-Shot Learning

Cited by 1