Check computer science papers: citations, claims and retractions

Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking

Chen, Y., Shang, J., Zhang, Z., Xie, Y., Sheng, J., Liu, T., Wang, S., Sun, Y., Wu, H., & Wang, H. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale

Koepke, A. S., Zverev, D., Ginosar, S., & Efros, A. A. (2026) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 0

Tell, don't show: Declarative facts influence how LLMs generalize

Meinke, A., & Evans, O. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models

Yan, Y., Shen, Y., Liu, Y., Jiang, J., Zhang, M., Shao, J., & Zhuang, Y. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Same Ranking, Different Winner: How Scoring Targets Shape LLM Memory Benchmarks

Panthi, S., & Abdelfattah, R. (2026) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 0

Teacher Self-Use Predicts Classroom Adoption of Generative AI Among Japanese High School Informatics Teachers

Inagaki, S. (2026) · IICE Official Conference Proceedings

Artificial Intelligence in EducationEducation and Technology Integration

Cited by 0

Evo-Bench: Can Language Models Improve Agent Harness?

Huang, L., Yang, C., Zhou, H., Song, H., Chen, Z., Le, R., Song, Y., Zhao, W. X., & Zhang, T. (2026) · arXiv

Evolutionary Algorithms and ApplicationsAI-based Problem Solving and Planning

Cited by 0

Automated Design of Agentic Systems: A Survey of Algorithms for Searching, Optimizing, and Evolving LLM Agents, Workflows, and Prompts

Madžar, M., & Mekterović, I. (2026) · Preprints.org

Evolutionary Algorithms and ApplicationsAI-based Problem Solving and Planning

Cited by 0

SEMAG: Self-Evolutionary Multi-Agent Code Generation

Peng, Y., Hou, H., Zhu, X., He, Y. T., & Yu, F. R. (2026) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 0

Elastic Weight Removal for Faithful and Abstractive Dialogue Generation

Daheim, N., Dziri, N., Sachan, M., Gurevych, I., & Ponti, E. M. (2023) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 0

Securing LLM-Agent Long-Term Memory Against Poisoning: Non-Malleable, Origin-Bound Authority with Machine-Checked Guarantees

Louck, Y. (2026) · arXiv

Security and Verification in ComputingBlockchain Technology Applications and Security

Cited by 0

Agent Lightning: Train ANY AI Agents with Reinforcement Learning

Luo, X., Zhang, Y., He, Z., Wang, Z., Zhao, S., Li, D., Qiu, L. K., & Yang, Y. (2025) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence Applications

Cited by 0

Integrated Information Theory (IIT) and Artificial Consciousness

Fallon, F. (2017) · Advances in Computational Intelligence and Robotics

Computability, Logic, AI AlgorithmsNeural dynamics and brain function

Cited by 0

Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents

Bei, Y., Wei, T., Ning, X., Zhao, Y., Liu, Z., Lin, X., Zhu, Y., Hamann, H., He, J., & Tong, H. (2026) · arXiv

Multimodal Machine Learning ApplicationsSpeech and dialogue systems

Cited by 0

Sampling-Efficient Test-Time Scaling: Self-Estimating the Best-of-N Sampling in Early Decoding

Wang, Y., Zhang, P., Huang, S., Yang, B., Zhang, Z., Huang, F., & Wang, R. (2025) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 0

Gottesman-Kitaev-Preskill codes: A lattice perspective

Conrad, J., Eisert, J., & Arzani, F. (2022) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 0

Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks

Xian, R. P., Lee, A. J., Lolla, S., Wang, V., Cui, Q., Ro, R., & Abbasi-Asl, R. (2024) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 0

AutoP2C: An LLM-Based Agent Framework for Code Repository Generation from Multimodal Content in Academic Papers

Lin, Z., Shen, Y., Cai, Q., Sun, H., Zhou, J., & Xiao, M. (2025) · arXiv

Software Engineering ResearchMultimodal Machine Learning Applications

Cited by 0

Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding

Yuan, L., Wang, J., Sun, H., Zhang, Y., & Lin, Y. (2025) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 0

EMO2: End-Effector Guided Audio-Driven Avatar Video Generation

Tian, L., Hu, S., Wang, Q., Zhang, B., & Bo, L. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisHuman Motion and Animation

Cited by 0

AI for Auto-Research: Roadmap & User Guide

Kong, L., Sun, X., Chow, W., Li, L., Lin, K. Q., Zhang, X. B., Wang, S., Li, R., Wu, Q., Gao, W., et al. (2026) · arXiv

Artificial Intelligence ApplicationsEthics and Social Impacts of AI

Cited by 0

Same Scrutiny, More Time: Eye Tracking Insights into Reviewing LLM-Labelled Code

Khojah, R., Neto, F. G. D. O., Mohamad, M., Frattini, J., & Leitner, P. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

NVIDIA, :, Blakeman, A., Basant, A., Khattar, A., Renduchintala, A., Bercovich, A., Ficek, A., Bjorlin, A., Taghibakhshi, A., et al. (2025) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0

PARL-MT: Learning to Call Functions in Multi-Turn Conversation with Progress Awareness

Chai, H., Cao, Z., Ran, M., Yang, Y., Lin, J., Peng, X., Wang, H., Ding, R., Wan, Z., Wen, M., et al. (2025) · arXiv

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 0