Check computer science papers: citations, claims and retractions

Retrieving Supporting Evidence for LLMs Generated Answers

Huo, S., Arabzadeh, N., & Clarke, C. L. A. (2023) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 4

Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes

Kumar, A., Agarwal, R., Geng, X., Tucker, G., & Levine, S. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 4

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Xin, H., Ren, Z. Z., Song, J., Shao, Z., Zhao, W., Wang, H., Liu, B., Zhang, L., Lu, X., Du, Q., et al. (2024) · arXiv

Mathematics, Computing, and Information ProcessingLogic, programming, and type systems

Cited by 4

Ubuntu as a complementary perspective for addressing epistemic (in)justice in medical machine learning

Ferlito, B., & De Proost, M. (2023) · Journal of Medical Ethics

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 4

Contrastive predictive coding for Anomaly Detection in Multi-variate Time Series Data

Pranavan, T., Sim, T., Ambikapathi, A., & Ramasamy, S. (2022) · arXiv

Anomaly Detection Techniques and ApplicationsTime Series Analysis and Forecasting

Cited by 4

Chaotic image encryption on GPU

Vihari, P. L. V., & Mishra, M. (2012) · Proceedings of the CUBE International Information Technology Conference

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 4

Perceptron ann control of array sensors and transmitters with different activation functions for 5G wireless systems

Senthilkumar, K. S., Pirapaharan, K., Julai, N., Hoole, P. R. P., Othman, A.-H., Harikrishnan, R., & Hoole, S. R. H. (2017) · 2017 International Conference on Signal Processing and Communication (ICSPC)

Direction-of-Arrival Estimation TechniquesNeural Networks and Applications

Cited by 4

Echoes of AI: Investigating the downstream effects of AI assistants on software maintainability

Borg, M., Hewett, D., Hagatulah, N., Couderc, N., Söderberg, E., Graham, D., Kini, U., & Farley, D. (2026) · Empirical Software Engineering

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 4

When2Call: When (not) to Call Tools

Ross, H., Mahabaleshwarkar, A. S., & Suhara, Y. (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)

Natural Language Processing TechniquesSpeech and dialogue systems

Cited by 4

Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models

Kim, S., Choi, S., & Jeong, M. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

Anomaly Detection in Graph Structured Data: A Survey

Lamichhane, P. B., & Eberle, W. (2024) · arXiv

Anomaly Detection Techniques and ApplicationsAdvanced Graph Neural Networks

Cited by 4

It might be balanced, but is it actually good? An Empirical Evaluation of Game Level Balancing

Rupp, F., Puddu, A., Becker-Asano, C., & Eckert, K. (2024) · 2024 IEEE Conference on Games (CoG)

Artificial Intelligence in GamesDigital Games and Media

Cited by 4

Experimenting with Model Solutions as a Support Mechanism

Nygren, H., Leinonen, J., Pirttinen, N., Leinonen, A., & Hellas, A. (2019) · Proceedings of the 1st UK & Ireland Computing Education Research Conference on - UKICER

Teaching and Learning ProgrammingOnline Learning and Analytics

Cited by 4

Natural Shell: An Assistant for End-User Scripting

Liu, X., Jiang, Y., Wu, L., & Wu, D. (2016) · International Journal of People-Oriented Programming

Spreadsheets and End-User ComputingSoftware Engineering Research

Cited by 4

Raindrop-Aware GAN: Unsupervised Learning for Raindrop-Contaminated Coastal Video Enhancement

Kim, J., Huh, D., Kim, T., Kim, J., Yoo, J., & Shim, J.-S. (2020) · Remote Sensing

Image Enhancement TechniquesAdvanced Image Processing Techniques

Cited by 4

Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model

Lin, H., Cho, J., Zala, A., & Bansal, M. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 4

Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents

Yu, Y., Yao, L., Xie, Y., Tan, Q., Feng, J., Li, Y., & Wu, L. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 4

syslrn: learning what to monitor for efficient anomaly detection

Sanvito, D., Siracusano, G., Santhanam, S., Gonzalez, R., & Bifulco, R. (2022) · Proceedings of the 2nd European Workshop on Machine Learning and Systems

Software System Performance and ReliabilityNetwork Security and Intrusion Detection

Cited by 4

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward

Fan, Z., Wang, Y., Polisetty, S., & Fung, Y. R. (2025) · Findings of the Association for Computational Linguistics: ACL 2025

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 4

Mechanistic Design and Scaling of Hybrid Architectures

Poli, M., Thomas, A. W., Nguyen, E., Ponnusamy, P., Deiseroth, B., Kersting, K., Suzuki, T., Hie, B., Ermon, S., Ré, C., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

Explaining Length Bias in LLM-Based Preference Evaluations

Hu, Z., Song, L., Zhang, J., Xiao, Z., Wang, T., Chen, Z., Yuan, N. J., Lian, J., Ding, K., & Xiong, H. (2025) · Findings of the Association for Computational Linguistics: EMNLP 2025

Recommender Systems and TechniquesSentiment Analysis and Opinion Mining

Cited by 4

Temporal Fact Reasoning over Hyper-Relational Knowledge Graphs

Ding, Z., Wu, J., Wu, J., Xia, Y., Xiong, B., & Tresp, V. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Advanced Graph Neural NetworksSemantic Web and Ontologies

Cited by 4

Look Before You Leap: A GUI-Critic-R1 Model for Pre-Operative Error Diagnosis in GUI Automation

Wanyan, Y., Zhang, X., Xu, H., Liu, H., Wang, J., Ye, J., Kou, Y., Yan, M., Huang, F., Yang, X., et al. (2025) · arXiv

Software Testing and Debugging TechniquesRobotic Process Automation Applications

Cited by 4

A Comparative Study on Recent Neural Spoofing Countermeasures for Synthetic Speech Detection

Wang, X., & Yamagishi, J. (2021) · arXiv

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 4