Check computer science papers: citations, claims and retractions

Not Every AI Problem is a Data Problem: We Should Be Intentional About Data Scaling

Rodchenko, T., Noy, N., & Scherrer, N. (2025) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 0

Planetary Terrain Datasets and Benchmarks for Rover Path Planning

Chancán, M., Banerjee, A., & Nikolakopoulos, G. (2025) · arXiv

Robotic Path Planning AlgorithmsSpacecraft Dynamics and Control

Cited by 0

SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents

Kutasov, J., Sun, Y., Colognese, P., van der Weij, T., Petrini, L., Zhang, C. B. C., Hughes, J., Deng, X., Sleight, H., Tracy, T., et al. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0

EasyControl: Adding Efficient and Flexible Control for Diffusion Transformer

Zhang, Y., Yuan, Y., Song, Y., Wang, H., & Liu, J. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 0

UniCoder: Scaling Code Large Language Model via Universal Code

Sun, T., Chai, L., Yang, J., Yin, Y., Guo, H., Liu, J., Wang, B., Yang, L., & Li, Z. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 0

ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data

Liu, Z., Xie, J., Ding, Z., Li, Z., Yang, B., Wu, Z., Wang, X., Sun, Q., Liu, S., Wang, W., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsInformation Retrieval and Search Behavior

Cited by 0

AgentOCR: Reimagining Agent History via Optical Self-Compression

Feng, L., Yang, F., Chen, F., Cheng, X., Xu, H., Wan, Z., Yan, M., & An, B. (2026) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 0

Practical Exploration of an Agent-Empowered Smart Library Service Platform——A Case Study of Wuhan University of Technology Library

Guo, Q., Zhao, F., & Feng, H. (2025) · Proceedings of the 2025 2nd International Conference on Artificial Intelligence and Future Education

Library Science and InformationWeb and Library Services

Cited by 0

Spatially entangled states of light in nonlinear waveguide arrays - INVITED

Raymond, A., Francesconi, S., Palomo, J., Filloux, P., Morassi, M., Lemaître, A., Raineri, F., Amanti, M., Ducci, S., & Baboux, F. (2023) · EPJ Web of Conferences

Quantum Information and CryptographySemiconductor Quantum Structures and Devices

Cited by 0

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think

Shen, Z., Tong, J., Yan, S., Shen, C., Chen, H., Ye, W., Hu, X., Miao, R., Wang, H., Zhao, J., et al. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Do LLM Agents Know How to Ground, Recover, and Assess? A Benchmark for Epistemic Competence in Information-Seeking Agents

Shao, J., Lin, Y., Lohani, M. P., Miao, Y., & Luo, B. (2025) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 0

DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning

Marjanović, S. V., Patel, A., Adlakha, V., Aghajohari, M., BehnamGhader, P., Bhatia, M., Khandelwal, A., Kraft, A., Krojer, B., Lù, X. H., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Biphoton Quantum State Tomography and Spin-orbit Conversion in C+L Telecom Bands

Youssef, M., Gounden, N., Ornelas, P., Nape, I., Forbes, A., & Ung, B. (2024) · 2024 IEEE International Conference on Quantum Computing and Engineering (QCE)

Quantum Information and CryptographyOrbital Angular Momentum in Optics

Cited by 0

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence

Meng, Y., Tang, L., Yu, F., Jia, J., Yan, G., Yang, P., & Xi, Z. (2025) · arXiv

Information and Cyber SecurityAdversarial Robustness in Machine Learning

Cited by 0

A Cost Model for Token Consumption of Hypermedia and the Model-Context-Protocol in Agentic Loops

Gross, C., & Revelle, M. (2026) · Proceedings of the 37th ACM Conference on Hypertext

Natural Language Processing TechniquesWeb Applications and Data Management

Cited by 0

LLM-Powered Decentralized Generative Agents with Adaptive Hierarchical Knowledge Graph for Cooperative Planning

Yang, H., Chen, J., Siew, M., Lorido-Botran, T., & Joe-Wong, C. (2025) · arXiv

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 0

Explore with Long-term Memory: A Benchmark and Multimodal LLM-based Reinforcement Learning Framework for Embodied Exploration

Wang, S., Liu, B., Gao, Z., Ma, L., Wang, X., Xie, Y., & Tan, X. (2026) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 0

Efficient Time Series Processing for Transformers and State-Space Models through Token Merging

Götz, L., Kollovieh, M., Günnemann, S., & Schwinn, L. (2024) · arXiv

Time Series Analysis and ForecastingTopic Modeling

Cited by 0

EmbedLLM: Learning Compact Representations of Large Language Models

Zhuang, R., Wu, T., Wen, Z., Li, A., Jiao, J., & Ramchandran, K. (2024) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 0

Agentic Plan Caching: Test-Time Memory for Fast and Cost-Efficient LLM Agents

Zhang, Q., Wornow, M., Wan, G., & Olukotun, K. (2025) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 0

Proceedings of the 2014 ACM conference on Security and privacy in wireless & mobile networks

(2014)

Mobile Ad Hoc NetworksCybersecurity and Information Systems

Cited by 0

AI Tutor, Online Course, or Both? A Randomized Experimental Pilot Study for Evaluation Capacity Building

Narine, L. K., & Diaz, J. M. (2026) · Education Sciences

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 0

Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live

Li, H., He, R., Mang, Q., Zhang, Q., Mao, H., Chen, X., Zhou, H., Zhang, H., Cheung, A., Gonzalez, J., et al. (2025) · arXiv

Parallel Computing and Optimization TechniquesSoftware System Performance and Reliability

Cited by 0

A Formulation of Recursive Self-Improvement and Its Possible Efficiency

Wang, W. (2018) · arXiv

Computability, Logic, AI AlgorithmsEvolutionary Algorithms and Applications

Cited by 0