Most cited computer science papers
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Evaluasi User Engagement dan User Experience pada Aplikasi Satu Sehat
Halim, F., & Suwandy, R. (2023) · Journal of Information System Research (JOSH)
Usability and User Interface DesignInnovative Human-Technology Interaction
Cited by 2
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Exploring Answer Set Programming for Provenance Graph-Based Cyber Threat Detection: A Novel Approach
Li, F., Zuo, F., & Gupta, G. (2025) · arXiv
Information and Cyber SecurityNetwork Security and Intrusion Detection
Cited by 2
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Synthetic continued pretraining
Yang, Z., Band, N., Li, S., Candès, E., & Hashimoto, T. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 2
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Measuring Non Monetary Innovation In Software: a case study in floss firms from Argentina
Motta, J., Morero, H. A., & Borrastero, C. (2019) · International Journal of Innovation
Open Source Software InnovationsInnovation and Knowledge Management
Cited by 2
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A Closed-Loop Personalized Learning Agent Integrating Neural Cognitive Diagnosis, Bounded-Ability Adaptive Testing, and LLM-Driven Feedback
Wang, Z., Zheng, X., & Zeng, C. (2025) · arXiv
Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics
Cited by 2
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Untying cable by combining 3D deep neural network with deep reinforcement learning
Fan, Z., Shao, W., Hayashi, T., & Ohashi, T. (2023) · Advanced Robotics
Reinforcement Learning in RoboticsRobot Manipulation and Learning
Cited by 2
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LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
Bai, Y., Tu, S., Zhang, J., Peng, H., Wang, X., Lv, X., Cao, S., Xu, J., Hou, L., Dong, Y., et al. (2024) · arXiv
Topic ModelingMultimodal Machine Learning Applications
Cited by 2
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LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Pan, Z., Wu, Q., Jiang, H., Xia, M., Luo, X., Zhang, J., Lin, Q., Rühle, V., Yang, Y., Lin, C.-Y., et al. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 2
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The Future of Continual Learning in the Era of Foundation Models: Three Key Directions
Bell, J., Quarantiello, L., Coleman, E. N., Li, L., Li, M., Madeddu, M., Piccoli, E., & Lomonaco, V. (2025) · arXiv
Domain Adaptation and Few-Shot LearningTopic Modeling
Cited by 2
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From Silos to Systems: Process-Oriented Hazard Analysis for AI Systems
Rismani, S., Dobbe, R., & Moon, A. (2024) · arXiv
Ethics and Social Impacts of AISafety Systems Engineering in Autonomy
Cited by 2
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Persona Features Control Emergent Misalignment
Wang, M., la Tour, T. D., Watkins, O., Makelov, A., Chi, R. A., Miserendino, S., Wang, J., Rajaram, A., Heidecke, J., Patwardhan, T., et al. (2025) · arXiv
Adversarial Robustness in Machine LearningEthics and Social Impacts of AI
Cited by 2
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A Reply on Responsibility and Repair in AI : Lessons From Outer Space, Agriculture and Gay Hookup Apps
Stevens, N., & Gieseking, J. J. (2026) · Transactions of the Institute of British Geographers
Ethics and Social Impacts of AIFeminism, Gender, and Intersectionality
Cited by 2
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VISREAS: Complex Visual Reasoning with Unanswerable Questions
Akter, S. N., Lee, S., Chang, Y., Bisk, Y., & Nyberg, E. (2024) · Findings of the Association for Computational Linguistics ACL 2024
Multimodal Machine Learning ApplicationsLogic, Reasoning, and Knowledge
Cited by 2
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Notifications on the Go: The Impact of Using the Blackboard
Chang, C.-W., & Farha, N. (2021) · International Journal of Technology in Teaching and Learning
Mobile Learning in EducationOnline and Blended Learning
Cited by 2
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The first step is the hardest: Pitfalls of Representing and Tokenizing Temporal Data for Large Language Models
Spathis, D., & Kawsar, F. (2023) · arXiv
Topic ModelingMachine Learning in Healthcare
Cited by 2
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The SWE-Bench Illusion: When State-of-the-Art LLMs Remember Instead of Reason
Liang, S., Garg, S., & Moghaddam, R. Z. (2026) · Proceedings of the IEEE/ACM 48th International Conference on Software Engineering: Software Engineering in Practice
Software Engineering ResearchTopic Modeling
Cited by 2
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On Accelerating Edge AI: Optimizing Resource-Constrained Environments
Sander, J., Cohen, A., Dasari, V. R., Venable, B., & Jalaian, B. (2025) · arXiv
Advanced Neural Network ApplicationsIoT and Edge/Fog Computing
Cited by 2
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UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation
Cheng, D., Huang, S., Bi, J., Zhan, Y., Liu, J., Wang, Y., Sun, H., Wei, F., Deng, D., & Zhang, Q. (2023) · arXiv
Topic ModelingDomain Adaptation and Few-Shot Learning
Cited by 2
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Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
Halawi, D., Wei, A., Wallace, E., Wang, T. T., Haghtalab, N., & Steinhardt, J. (2024) · arXiv
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 2
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Low Resource Question Answering: An Amharic Benchmarking Dataset
Taffa, T. A., Usbeck, R., & Assabie, Y. (2024) · Proceedings of the Language Resources and Evaluation Conference
Topic ModelingNatural Language Processing Techniques
Cited by 2
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FullStack Bench: Evaluating LLMs as Full Stack Coders
Bytedance-Seed-Foundation-Code-Team, :, Cheng, Y., Chen, J., Chen, J., Chen, L., Chen, L., Chen, W., Chen, Z., Geng, S., et al. (2024) · arXiv
Software Engineering ResearchTopic Modeling
Cited by 2
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Spike No More: Stabilizing the Pre-training of Large Language Models
Takase, S., Kiyono, S., Kobayashi, S., & Suzuki, J. (2023) · arXiv
Topic ModelingStochastic Gradient Optimization Techniques
Cited by 2
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Tablet app for child cognitive assessment in low and middle income countries
Francis-Lyon, P., Attiga, Y., Manjunath, R., Ramasubramanian, U., Chaudhuri, V., Nguyen, T., Xu, X., Zeng, S., Abubakar, A., & Newton, C. R. (2017) · 2017 IEEE Global Humanitarian Technology Conference (GHTC)
ICT in Developing CommunitiesChild Nutrition and Water Access
Cited by 2
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Navigating Rifts in Human-LLM Grounding: Study and Benchmark
Shaikh, O., Mozannar, H., Bansal, G., Fourney, A., & Horvitz, E. (2025) · arXiv
Speech and dialogue systemsLanguage, Discourse, Communication Strategies
Cited by 2
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