Check computer science papers: citations, claims and retractions

DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation

Wang, Y., Wang, L., Deng, Y., Wu, K., Xiao, Y., Yao, H., Kang, L., Ye, H., Jing, Y., & Bing, L. (2026) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 0

Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights

Parashar, S., Olson, B., Khurana, S., Li, E., Ling, H., Caverlee, J., & Ji, S. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

FullDiT: Multi-Task Video Generative Foundation Model with Full Attention

Ju, X., Ye, W., Liu, Q., Wang, Q., Wang, X., Wan, P., Zhang, D., Gai, K., & Xu, Q. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 0

DORA Explorer: Improving the Exploration Ability of LLMs Without Training

Gurjar, P., Ishmam, M. F., & Marino, K. (2026) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 0

Why Are AI Agent–Involved Pull Requests (Fix-Related) Remain Unmerged? An Empirical Study

Alam, K., Mondal, S., & Roy, B. (2026) · Proceedings of the 23rd International Conference on Mining Software Repositories

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

From Approval to Abuse: Privilege Escalation Attacks on Harness-Protected Coding Agents

Yang, X., Zhang, Y., Liu, J., Chen, Y., Cao, Y., Hooi, B., & Zhang, J. (2026) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 0

A Unified Approach to Routing and Cascading for LLMs

Dekoninck, J., Baader, M., & Vechev, M. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

SAST Implementation for Evaluating LLM-Generated Code Quality using Prompt Engineering

Abdillah, M. L., & Hardiani, T. (2026) · SISTEMASI

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 0

End-to-End Test-Time Training for Long Context

Tandon, A., Dalal, K., Li, X., Koceja, D., Rød, M., Buchanan, S., Wang, X., Leskovec, J., Koyejo, S., Hashimoto, T., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

From Correlation to Intervention: A Survey on Log-Based Causal Analysis for Security and AIOps

Zhu, Y., Li, X., Suo, J., Yin, Y., & Huang, C. (2026) · 2026 International Conference on AI in Education Technology and Applications (AIETA)

Software System Performance and ReliabilityNetwork Security and Intrusion Detection

Cited by 0

What Drives Interactive Improvement from Feedback?

Cupiał, B., Łojek, J., Garstecki, M., Pobłocki, S., Ziarko, A., & Miłoś, P. (2026) · arXiv

Natural Language Processing TechniquesIntelligent Tutoring Systems and Adaptive Learning

Cited by 0

From Tool to Method: Developing AI Literacy in an Upper-Level History Course

Dumančić, M., & Stickle, T. (2026) · Journal of Teaching and Learning with Technology

Artificial Intelligence in EducationDigital literacy in education

Cited by 0

Projectional Decoding: Towards Semantic-Aware LLM Generation

Chen, B., López, J. A. H., & Babikian, A. A. (2026) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 0

ILION: Deterministic Pre-Execution Safety Gates for Agentic AI Systems

Chitan, F. A. (2026) · arXiv

Adversarial Robustness in Machine LearningAccess Control and Trust

Cited by 0

LoCoMo-Plus: Beyond-Factual Cognitive Memory Evaluation Framework for LLM Agents

Li, Y., Guo, W., Zhang, L., Xu, R., Huang, M., Liu, H., Xu, L., Xu, Y., & Liu, J. (2026) · arXiv

Speech and dialogue systemsAI in Service Interactions

Cited by 0

Demonstration Attack against In-Context Learning for Code Intelligence

Ge, Y., Sun, W., Lou, Y., Fang, C., Zhang, Y., Li, Y., Zhang, X., Liu, Y., Zhao, Z., & Chen, Z. (2024) · arXiv

Adversarial Robustness in Machine LearningSoftware Engineering Research

Cited by 0

Making AI Visible, Not Vanished: How AI Policies Reshape Developer Experience on GitHub

Chen, Y., Zimmermann, T., & Trinkenreich, B. (2026) · arXiv

Open Source Software InnovationsSoftware Engineering Research

Cited by 0

PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS SMARTPHONE PADA MATERI KONSEP REAKSI REDUKSI DAN OKSIDASI

Herawan, R. S. K. N., Hana, M. N., & Halimatul, H. S. (2023) · Jurnal Riset dan Praktik Pendidikan Kimia

Multimedia Learning SystemsEducational Methods and Outcomes

Cited by 0

NovelQA: Benchmarking Question Answering on Documents Exceeding 200K Tokens

Wang, C., Ning, R., Pan, B., Wu, T., Guo, Q., Deng, C., Bao, G., Hu, X., Zhang, Z., Wang, Q., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

$μ$PC: Scaling Predictive Coding to 100+ Layer Networks

Innocenti, F., Achour, E. M., & Buckley, C. L. (2025) · arXiv

Neural Networks and ApplicationsAdvanced Memory and Neural Computing

Cited by 0

Diagnosing Retrieval vs. Utilization Bottlenecks in LLM Agent Memory

Yuan, B., Su, Y., & Yao, K. (2026) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0

Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Merrill, M. A., Shaw, A. G., Carlini, N., Li, B., Raj, H., Bercovich, I., Shi, L., Shin, J. Y., Walshe, T., Buchanan, E. K., et al. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 0

Auditing Harness Tampering in Self-Improving Agents

Wang, X., Zhang, X., & Shao, J. (2026) · arXiv

Adversarial Robustness in Machine LearningSoftware Testing and Debugging Techniques

Cited by 0

Edge-Constrained Video Analytics: A Comprehensive Survey on Detection, Tracking, and Recognition

Toshpulatov, M. A., Lee, W., & Cho, J. (2026) · SSRN Electronic Journal

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 0