Check computer science papers: citations, claims and retractions

metabench -- A Sparse Benchmark of Reasoning and Knowledge in Large Language Models

Kipnis, A., Voudouris, K., Buschoff, L. M. S., & Schulz, E. (2024) · arXiv

Topic ModelingMachine Learning and Data Classification

Cited by 1

Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles

Huang, K.-H., Laban, P., Fabbri, A. R., Choubey, P. K., Joty, S., Xiong, C., & Wu, C.-S. (2023) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 1

Cipher Image Damage: An Application of Filters

Flores-Carapia, R., Silva-García, V. M., Luna-Benoso, B., & Rentería-Márquez, C. (2015) · Polibits

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 1

From Self-Learning to Self-Evolving Architectures in Large Language Models: A Short Survey

Sapkota, R., Roumeliotis, K. I., Pokhrel, S., & Karkee, M. (2025)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1

TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents

Li, K., Yu, X., Ni, Z., Zeng, Y., Xu, Y., Zhang, Z., Li, X., Sang, J., Duan, X., Wang, X., et al. (2026) · arXiv

Speech and dialogue systemsAI in Service Interactions

Cited by 1

DrDiff: Dynamic Routing Diffusion with Hierarchical Attention for Breaking the Efficiency-Quality Trade-off

Zhang, J., Fan, Y., Cai, K., Huang, Z., Sun, X., Wang, J., Tang, C., & Wang, K. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Generative Adversarial Networks and Image SynthesisTopic Modeling

Cited by 1

TrustSQL: Benchmarking Text-to-SQL Reliability with Penalty-Based Scoring

Lee, G., Chay, W., Cho, S., & Choi, E. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1

A Usage-centric Take on Intent Understanding in E-Commerce

Zhou, W., Li, T., Vougiouklis, P., Steedman, M., & Pan, J. Z. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Recommender Systems and TechniquesSemantic Web and Ontologies

Cited by 1

Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination

Wu, M., Zhang, Z., Dong, Q., Xi, Z., Zhao, J., Jin, S., Fan, X., Zhou, Y., Lv, H., Zhang, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

MiVOLO: Multi-input Transformer for Age and Gender Estimation

Kuprashevich, M., & Tolstykh, I. (2023) · arXiv

Face recognition and analysisAdvanced Neural Network Applications

Cited by 1

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack

Wang, H., Li, H., Mang, Q., Cheung, A., Sen, K., & Song, D. (2026) · arXiv

Adversarial Robustness in Machine LearningSoftware Testing and Debugging Techniques

Cited by 1

Natural Emergent Misalignment from Reward Hacking in Production RL

MacDiarmid, M., Wright, B., Uesato, J., Benton, J., Kutasov, J., Price, S., Bouscal, N., Bowman, S., Bricken, T., Cloud, A., et al. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 1

A-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory

Wei, Q., Yang, T., Wang, Y., Li, X., Li, L., Yin, Z., Zhan, Y., Holz, T., Lin, Z., & Wang, X. (2025) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1

From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents

Ahn, J., & Kim, M. (2026) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 1

Cognitive Memory in Large Language Models

Shan, L., Luo, S., Zhu, Z., Yuan, Y., & Wu, Y. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Preble: Efficient Distributed Prompt Scheduling for LLM Serving

Srivatsa, V., He, Z., Abhyankar, R., Li, D., & Zhang, Y. (2024) · arXiv

Cloud Computing and Resource ManagementParallel Computing and Optimization Techniques

Cited by 1

Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks

Wang, C., Duan, H., Zhang, S., Lin, D., & Chen, K. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

DebateQA: Evaluating Question Answering on Debatable Knowledge

Xu, R., Qi, X., Qi, Z., Xu, W., & Guo, Z. (2026) · Findings of the Association for Computational Linguistics: EACL 2026

Topic ModelingInformation Retrieval and Search Behavior

Cited by 1

Learning to Abstain: Reliable Medical Image Segmentation With Rejection Option

Sanisoglu, M. A., Navab, N., & Kim, S. T. (2026) · IEEE Access

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1

TRACE: Evaluating Execution Efficiency of LLM-Based Code Translation

Gong, Z., Sun, Z., Huang, D., Liang, Q., Zhang, J. M., & Hao, D. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Software Engineering ResearchNatural Language Processing Techniques

Cited by 1

Using personalized support & school-based study groups to increase teachers’ participation in MOOCs: Findings from two European pilot projects

Hertz, B., & Engelhardt, K. (2021) · IUL Research

Online Learning and AnalyticsOnline and Blended Learning

Cited by 1

Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models

Lamb, A., Islam, R., Efroni, Y., Didolkar, A., Misra, D., Foster, D., Molu, L., Chari, R., Krishnamurthy, A., & Langford, J. (2022) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 1

A State-Aware Dual-Tool Architecture for Improved Tool Use in Multi-Turn LLM Dialogue

Pałgan, B., Wawryszczuk, M., Chwał, J., Tkacz, E., & Dzik, R. (2026) · Applied Sciences

Speech and dialogue systemsArtificial Intelligence Applications

Cited by 1

AdvAgent: Controllable Blackbox Red-teaming on Web Agents

Xu, C., Kang, M., Zhang, J., Liao, Z., Mo, L., Yuan, M., Sun, H., & Li, B. (2024) · arXiv

Adversarial Robustness in Machine LearningWeb Application Security Vulnerabilities

Cited by 1