Check computer science papers: citations, claims and retractions

Environment-in-the-Loop: Rethinking Code Migration with LLM-based Agents

Li, X., Fei, Z., Ma, Y., Zhang, J., Federica, S., & Ye, H. (2026) · arXiv

Software Engineering ResearchModel-Driven Software Engineering Techniques

Cited by 0

Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Model

Lab, N., :, Yang, C., Huang, C., Lan, F., Chen, H., Zhou, H., Song, H., Cao, J., Zhu, J., et al. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Reasoning Models Can Be Effective Without Thinking

Ma, W., He, J., Snell, C., Griggs, T., Min, S., & Zaharia, M. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Improving Controller Generalization with Dimensionless Markov Decision Processes

Charvet, V., Stein, S., & Murray-Smith, R. (2025) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 0

Boosting Chart-to-Code Generation in MLLM via Dual Preference-Guided Refinement

Zhang, Z., Cao, Y., & Liao, L. (2025) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 0

Towards Sustainable Wildlife Conservation: Automatic Recognition of Endangered Animal Behavior Using a Multimodal Contrastive Learning Framework

Liu, S., Xu, A., & Hou, Z. (2026) · Sustainability

Human Pose and Action RecognitionMultimodal Machine Learning Applications

Cited by 0

IFCMemoryBench: Evaluating Long-Term Memory of LLM-Based Agents in BIM Information Retrieval

Du, C., Vosseler, A., Mazza, F., & Borrmann, A. (2026) · arXiv

Topic ModelingAI-based Problem Solving and Planning

Cited by 0

Rethinking Thinking Tokens: LLMs as Improvement Operators

Madaan, L., Didolkar, A., Gururangan, S., Quan, J., Silva, R., Salakhutdinov, R., Zaheer, M., Arora, S., & Goyal, A. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

More Capable, Less Cooperative? When LLMs Fail At Zero-Cost Collaboration

Yadav, A., Black, S., & Sourbut, O. (2026) · arXiv

Multi-Agent Systems and NegotiationGame Theory and Applications

Cited by 0

HELIX: Model-Harness Co-evolution for Recursive Self-Improvement

Fan, T., & Huang, C. (2026) · arXiv

Software Engineering ResearchEvolutionary Algorithms and Applications

Cited by 0

Autogenesis: A Self-Evolving Agent Protocol

Zhang, W., Zhao, Z., Wen, H., Wu, Y., Guo, C., Yin, M., & An, B. (2026) · arXiv

AI-based Problem Solving and PlanningMulti-Agent Systems and Negotiation

Cited by 0

GRASP: Gated Regression-Aware Skill Proposer for Self-Improving LLM Agents

Moll, J., Corbeil, J.-P., Pan, J., Hadamitzky, M., Rueckert, D., Adams, L., & Bressem, K. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence in Healthcare and Education

Cited by 0

Measuring Baseline Web Security Posture: Tier-1 HTTP Security Header Adoption in the Maldives and the WSHS-B Governance Metric

Waheed, L., & Alazab, A. (2026) · Future Internet

Web Application Security VulnerabilitiesInformation and Cyber Security

Cited by 0

RAGShield: Detecting Numerical Claim Manipulation in Government RAG Systems

Patil, K. (2026) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 0

A Closed-Loop Modular Language Agent with Step Verification and Local Correction for Multi-Step Task Solving

Li, H., Feng, L., & Wang, D. (2026) · Electronics

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 0

The ARC of Progress towards AGI: A Living Survey of Abstraction and Reasoning

Vahdati, S., Aioanei, A., Suresh, H., & Lehmann, J. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 0

Integrating AI literacy into information culture formation for pre-service teachers: a quasi-experimental study with a reflexive-adaptive model

Haytboyeva, M., Shihova, H., & Saidmamatov, O. (2026) · Frontiers in Education

Digital literacy in educationLibrary Science and Information Literacy

Cited by 0

Efficient and Accurate Prompt Optimization: the Benefit of Memory in Exemplar-Guided Reflection

Yan, C., Wang, J., Zhang, L., Zhao, R., Wu, X., Xiong, K., Liu, Q., Kang, G., & Kang, Y. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Advanced shell programming

Joy, M., Jarvis, S., & Luck, M. (2002) · Introducing UNIX and Linux

Teaching and Learning ProgrammingEngineering and Information Technology

Cited by 0

Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents

Chen, S. (2026) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0

Spine: Compiling Subtask Trees into Structured Context for Long-Horizon Coding Agents

Xiang, J., Chen, K., Zhang, L., & Zhang, Y. (2026) · arXiv

Software Engineering ResearchAI-based Problem Solving and Planning

Cited by 0

When Sub-Agents Work in Parallel: The Promises and Pitfalls of Dynamic Concurrency in Long-Horizon Coding Tasks

Li, H., Li, H., Jiang, Z., & Lou, Y. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

An Input-Queueing TSN Switching Architecture to Achieve Zero Packet Loss for Timely Traffic

Li, M., Deng, L., & Han, Y. S. (2022) · arXiv

Network Time Synchronization TechnologiesNetwork Traffic and Congestion Control

Cited by 0

ICBCBench: An Industry Consortium Benchmark for Financial Deep Research

Li, W., Tang, Z., He, Y., Wang, C., Feng, L., Sun, X., Liu, D., Wen, Z., Wei, H., Wang, J., et al. (2026) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0