Check computer science papers: citations, claims and retractions

Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities

Amara, K., Klein, L., Lüth, C., Jäger, P., Strobelt, H., & El-Assady, M. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 1

Reward-Guided Speculative Decoding for Efficient LLM Reasoning

Liao, B., Xu, Y., Dong, H., Li, J., Monz, C., Savarese, S., Sahoo, D., & Xiong, C. (2025) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1

ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews

D'Arcy, M., Ross, A., Bransom, E., Kuehl, B., Bragg, J., Hope, T., & Downey, D. (2023) · arXiv

Topic ModelingSoftware Engineering Research

Cited by 1

The Tyranny of Possibilities in the Design of Task-Oriented LLM Systems: A Scoping Survey

Dhamani, D., & Maher, M. L. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

An Efficient Framework for Integrating DevOps Practices in Network Configuration and Monitoring

Jose, J., & Shenoy, G. S. (2024) · 2024 3rd International Conference for Innovation in Technology (INOCON)

Software-Defined Networks and 5GSoftware System Performance and Reliability

Cited by 1

Self-Boosting Large Language Models with Synthetic Preference Data

Dong, Q., Dong, L., Zhang, X., Sui, Z., & Wei, F. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget

Dorner, F. E., & Hardt, M. (2024) · arXiv

Machine Learning and Data ClassificationMachine Learning and Algorithms

Cited by 1

RewardBench 2: Advancing Reward Model Evaluation

Malik, S., Pyatkin, V., Land, S., Morrison, J., Smith, N. A., Hajishirzi, H., & Lambert, N. (2025) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1

The Initial Screening Order Problem

Alvarez, J. M., Mastropietro, A., & Ruggieri, S. (2023) · arXiv

Ethics and Social Impacts of AIGame Theory and Voting Systems

Cited by 1

Outcome-based Exploration for LLM Reasoning

Song, Y., Kempe, J., & Munos, R. (2025) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 1

Uncertainty Quantification in Deep Residual Neural Networks

Wandzik, L., Garcia, R. V., & Krüger, J. (2020) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 1

Secure DBMS Auditor

Schaefer, M., Hubbard, B., Sterne, D., Haley, T., & McAuliffe, N. (1990)

Access Control and TrustSecurity and Verification in Computing

Cited by 1

On robustness in multimodal learning

McKinzie, B., Cheng, J., Shankar, V., Yang, Y., Shlens, J., & Toshev, A. (2023) · arXiv

Multimodal Machine Learning ApplicationsAdversarial Robustness in Machine Learning

Cited by 1

USER-CENTERED DESIGN AND USABILITY EVALUATION OF A CANCER PREVENTION WEB APPLICATION: AN ITERATIVE APPROACH IN GERMANY

Carrera, P., Elias, O., Zhang, R., Norajitra, T., Goncalves, A., & Maier-Hein, K. (2025) · medRxiv

Usability and User Interface DesignMobile Health and mHealth Applications

Cited by 1

Lil-Bevo: Explorations of Strategies for Training Language Models in More Humanlike Ways

Govindarajan, V. S., Rodriguez, J. D., Bostrom, K., & Mahowald, K. (2023) · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning

Topic ModelingNatural Language Processing Techniques

Cited by 1

Detecting the Insider Threat with Long Short Term Memory (LSTM) Neural Networks

Lopez, E., & Sartipi, K. (2020) · arXiv

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 1

Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks

Sarukkai, V., Xie, Z., & Fatahalian, K. (2025) · arXiv

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 1

On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents

Huang, J.-T., Zhou, J., Jin, T., Zhou, X., Chen, Z., Wang, W., Yuan, Y., Lyu, M. R., & Sap, M. (2024) · arXiv

Multi-Agent Systems and NegotiationNatural Language Processing Techniques

Cited by 1

Robustly Improving LLM Fairness in Realistic Settings via Interpretability

Karvonen, A., & Marks, S. (2025) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 1

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning

Suárez, J., Isola, P., Choe, K. W., Bloomin, D., Li, H. X., Pinnaparaju, N., Kanna, N., Scott, D., Sullivan, R., Shuman, R. S., et al. (2023) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 1

M+: Extending MemoryLLM with Scalable Long-Term Memory

Wang, Y., Krotov, D., Hu, Y., Gao, Y., Zhou, W., McAuley, J., Gutfreund, D., Feris, R., & He, Z. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

LLM Query Scheduling with Prefix Reuse and Latency Constraints

Dexter, G., Tang, S., Baarzi, A. F., Song, Q., Dharamsi, T., & Gupta, A. (2025) · arXiv

Cloud Computing and Resource ManagementAdvanced Database Systems and Queries

Cited by 1

AI developers, associations, and the academic community

Chinen, M. (2023) · The International Governance of Artificial Intelligence

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 1

ReXGradient-160K: A Large-Scale Publicly Available Dataset of Chest Radiographs with Free-text Reports

Zhang, X., Acosta, J. N., Miller, J., Huang, O., & Rajpurkar, P. (2025) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 1