Check computer science papers: citations, claims and retractions

Humans are Missing from AI Coding Agent Research

Wang, Z. Z., Yang, J., Lieret, K., Tartaglini, A., Chen, V., Wei, Y., Wang, Z., Zhang, L., Narasimhan, K., Schmidt, L., et al. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning

Cheng, M., Yu, S., Wang, D., Li, Q., Tao, X., Ouyang, J., Luo, Y., Zhou, Y., Liu, Q., & Chen, E. (2025) · arXiv

Reinforcement Learning in RoboticsNatural Language Processing Techniques

Cited by 0

Hindsight: Structured Agent Memory that Retains, Recalls, and Reflects

Latimer, C., Boschi, N., Neeser, A., Bartholomew, C., Srivastava, G., Wang, X., & Ramakrishnan, N. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 0

The Promptware Kill Chain: How Prompt Injections Gradually Evolved Into a Multistep Malware Delivery Mechanism

Brodt, O., Feldman, E., Schneier, B., & Nassi, B. (2026) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 0

Multimodal Promptable Token Merging for Diffusion Models

Hong, C.-Y., & Liu, T.-L. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 0

Limits to scalable evaluation at the frontier: LLM as Judge won't beat twice the data

Dorner, F. E., Nastl, V. Y., & Hardt, M. (2024) · arXiv

Machine Learning and Data ClassificationMachine Learning and Algorithms

Cited by 0

On Effectiveness and Efficiency of Agentic Tool-calling and RL Training

Liu, T., Qian, C., Cief, M., He, Y., Dan, D., Aletras, N., & Kazai, G. (2026) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 0

Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence

György, A., Lattimore, T., Lazić, N., & Szepesvári, C. (2025) · arXiv

Logic, Reasoning, and KnowledgeAI-based Problem Solving and Planning

Cited by 0

DDL: A Large-Scale Dataset for Deepfake Detection and Localization in Diversified Real-World Scenarios

Miao, C., Zhang, Y., Gao, W., Tan, Z., Feng, W., Luo, M., Li, J., Liu, A., Diao, Y., Chu, Q., et al. (2025) · arXiv

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

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Evaluating the Impact of AI-Based Software Development Tools on Programming Efficiency Among Tertiary Computing Students

Torres, J. C. G., Lacorte, A. M., & Calvez, J. P. G. (2026) · 2026 12th International Conference on Education and Training Technologies (ICETT)

Teaching and Learning ProgrammingSoftware Engineering Research

Cited by 0

Exploring Generative AI Use and Perceptions Among Students With and Without Disabilities in Higher Education

Waterfield, D. A., Ferreira de Vasconcellos, J., Crawford, M., Doyle, M., Taggart, J., Bayraktar, B., & Henry, D. (2026) · Journal of Special Education Technology

Artificial Intelligence in EducationDisability Education and Employment

Cited by 0

Towards Reliable Detection of LLM-Generated Texts: A Comprehensive Evaluation Framework with CUDRT

Tao, Z., Chen, Y., Xi, D., Li, Z., & Xu, W. (2024) · arXiv

Authorship Attribution and ProfilingDigital Media Forensic Detection

Cited by 0

Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining

Lin, L., Bai, Y., & Mei, S. (2023) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 0

Semantic Probabilistic Control of Language Models

Ahmed, K., Belem, C. G., Smyth, P., & Singh, S. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

CacheClip: Accelerating RAG with Effective KV Cache Reuse

Yang, B., Leng, Q., Zeng, J., & Wu, Z. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Toxicidade em Chats de Live Streaming: Um Estudo Comparativo com Coleta Síncrona em Twitch, YouTube e Kick

Cardoso, R., & Silva, C. A. (2026) · Anais do XV Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2026)

Hate Speech and Cyberbullying DetectionSwearing, Euphemism, Multilingualism

Cited by 0

RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System

Wang, Y., Xie, T., Shen, K., Wang, M., & Yang, L. (2026) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 0

Automatic Code Plagiarism Detection using AST and Machine Learning

Pavani, K., Kathyayani, M. S., Kousar, K. H., Lahari, K. P., Pavani, K., & Bai, R. (2026) · International Journal of Scientific Research in Science Engineering and Technology

Software Engineering ResearchAcademic integrity and plagiarism

Cited by 0

SemantiLynx: context based icons for mobile web navigation and directed search tasks

Setlur, V. (2010) · Proceedings of the 12th international conference on Human computer interaction with mobile devices and services

Data Visualization and AnalyticsUsability and User Interface Design

Cited by 0

Who Broke Me? Execution-Guided Repair of Behavioral Dependency Breaks

Chen, J., Bi, T., Wang, Y., & Thongtanunam, P. (2026) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 0

Git Context Controller: Manage the Context of LLM-based Agents like Git

Wu, J., Hu, M., Zhu, J., Pan, J., Liu, Y., Xu, M., & Jin, Y. (2025) · arXiv

Software Engineering ResearchAI-based Problem Solving and Planning

Cited by 0

Mem-α: Learning Memory Construction via Reinforcement Learning

Wang, Y., Takanobu, R., Liang, Z., Mao, Y., Hu, Y., McAuley, J., & Wu, X. (2025) · arXiv

Topic ModelingAI-based Problem Solving and Planning

Cited by 0

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives

Wang, Q., Ke, J., Tomizuka, M., Chen, Y., Keutzer, K., & Xu, C. (2025) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0

Coverage, Not Credit: Failure-Credit Routing of Zeroth-Order Perturbation Budgets Does Not Improve On-Pool Sample Efficiency for LLM Agents

Ge, Y. (2026) · arXiv

Reinforcement Learning in RoboticsMetaheuristic Optimization Algorithms Research

Cited by 0