Check computer science papers: citations, claims and retractions

CodePlan: Repository-Level Coding using LLMs and Planning

Bairi, R., Sonwane, A., Kanade, A., C., V. D., Iyer, A., Parthasarathy, S., Rajamani, S., Ashok, B., & Shet, S. (2024) · Proceedings of the ACM on Software Engineering

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 92

An online POMDP algorithm for complex multiagent environments

Paquet, S., Tobin, L., & Chaib-draa, B. (2005) · Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 92

Adaptive Routing for Sensor Networks using Reinforcement Learning

Wang, P., & Wang, T. (2006) · The Sixth IEEE International Conference on Computer and Information Technology (CIT'06)

Energy Efficient Wireless Sensor NetworksSecurity in Wireless Sensor Networks

Cited by 92

ARB: Advanced Reasoning Benchmark for Large Language Models

Sawada, T., Paleka, D., Havrilla, A., Tadepalli, P., Vidas, P., Kranias, A., Nay, J. J., Gupta, K., & Komatsuzaki, A. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 92

Is ChatGPT Equipped with Emotional Dialogue Capabilities?

Zhao, W., Zhao, Y., Lu, X., Wang, S., Tong, Y., & Qin, B. (2023) · arXiv

Speech and dialogue systemsEmotion and Mood Recognition

Cited by 92

TCP implementations and false time out detection in OBS networks

Yu, X., Qiao, C., & Liu, Y. (2005) · IEEE INFOCOM 2004

Network Traffic and Congestion ControlAdvanced Optical Network Technologies

Cited by 92

Autonomy in surgical robots and its meaningful human control

Ficuciello, F., Tamburrini, G., Arezzo, A., Villani, L., & Siciliano, B. (2019) · Paladyn, Journal of Behavioral Robotics

Ethics and Social Impacts of AIEthics and bioethics in healthcare

Cited by 92

Directly Discriminatory Algorithms

Adams‐Prassl, J., Binns, R., & Kelly‐Lyth, A. (2023) · The Modern Law Review

Ethics and Social Impacts of AIDiscrimination and Equality Law

Cited by 92

Phenaki: Variable Length Video Generation From Open Domain Textual Description

Villegas, R., Babaeizadeh, M., Kindermans, P.-J., Moraldo, H., Zhang, H., Saffar, M. T., Castro, S., Kunze, J., & Erhan, D. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 92

Emotion recognition from physiological signals

GOUIZI, K., BEREKSI REGUIG, F., & MAAOUI, C. (2011) · Journal of Medical Engineering & Technology

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 92

Analyzing and assessing explainable AI models for smart agriculture environments

Cartolano, A., Cuzzocrea, A., & Pilato, G. (2024) · Multimedia Tools and Applications

Explainable Artificial Intelligence (XAI)Smart Agriculture and AI

Cited by 92

The EMory BrEast imaging Dataset (EMBED): a racially diverse, granular dataset of 3.4 million screening and diagnostic mammographic images

Jeong, J. J., Vey, B. L., Bhimireddy, A., Kim, T., Santos, T., Correa, R., Dutt, R., Mosunjac, M., Oprea-Ilies, G., Smith, G., et al. (2023) · Radiology Artificial Intelligence

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 92

Retrieval-Augmented Generation (RAG)

Klesel, M., & Wittmann, H. F. (2025) · Business & Information Systems Engineering

Information Retrieval and Search BehaviorTopic Modeling

Cited by 92

A Human Activity Recognition Algorithm Based on Stacking Denoising Autoencoder and LightGBM

Gao, X., Luo, H., Wang, Q., Zhao, F., Ye, L., & Zhang, Y. (2019) · Sensors

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 92

Fog in Comparison to Cloud: A Survey

P.Saharan, K., & Kumar, A. (2015) · International Journal of Computer Applications

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 92

Language Models as Agent Models

Andreas, J. (2022) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 92

Cluster analysis in illness perception research: A Monte Carlo study to identify the most appropriate method

Clatworthy, J., Hankins, M., Buick, D., Weinman, J., & Horne, R. (2007) · Psychology & Health

Advanced Clustering Algorithms ResearchPsychometric Methodologies and Testing

Cited by 92

Habitat-Matterport 3D Semantics Dataset

Yadav, K., Ramrakhya, R., Ramakrishnan, S. K., Gervet, T., Turner, J., Gokaslan, A., Maestre, N., Chang, A. X., Batra, D., Savva, M., et al. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisReinforcement Learning in Robotics

Cited by 92

Wireless Network Intelligence at the Edge

Park, J., Samarakoon, S., Bennis, M., & Debbah, M. (2019) · Proceedings of the IEEE

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 92

Deep learning-based classification and mutation prediction from histopathological images of hepatocellular carcinoma

Liao, H., Long, Y., Han, R., Wang, W., Xu, L., Liao, M., Zhang, Z., Wu, Z., Shang, X., Li, X., et al. (2020) · Clinical and Translational Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 92

Open-Sourced Reinforcement Learning Environments for Surgical Robotics

Richter, F., Orosco, R. K., & Yip, M. C. (2019) · arXiv

Reinforcement Learning in RoboticsSurgical Simulation and Training

Cited by 92

CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

Puri, R., Kung, D. S., Janssen, G., Zhang, W., Domeniconi, G., Zolotov, V., Dolby, J., Chen, J., Choudhury, M., Decker, L., et al. (2021) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 92

Simultaneous localization and mapping using ambient magnetic field

Vallivaara, I., Haverinen, J., Kemppainen, A., & Roning, J. (2010) · 2010 IEEE Conference on Multisensor Fusion and Integration

Robotics and Sensor-Based LocalizationIndoor and Outdoor Localization Technologies

Cited by 92

RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs

Chaudhari, S., Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., Deshpande, A., & da Silva, B. C. (2024) · arXiv

Reinforcement Learning in RoboticsNatural Language Processing Techniques

Cited by 92