Check computer science papers: citations, claims and retractions

Agents: An Open-source Framework for Autonomous Language Agents

Zhou, W., Jiang, Y. E., Li, L., Wu, J., Wang, T., Qiu, S., Zhang, J., Chen, J., Wu, R., Wang, S., et al. (2023) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 21

Proof Artifact Co-training for Theorem Proving with Language Models

Han, J. M., Rute, J., Wu, Y., Ayers, E. W., & Polu, S. (2021) · arXiv

Logic, programming, and type systemsMathematics, Computing, and Information Processing

Cited by 21

Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability

Metcalf, J., Singh, R., Moss, E., Tafesse, E., & Watkins, E. A. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 21

Robust Prediction of Non-home Discharge After Thoracolumbar Spine Surgery With Ensemble Machine Learning and Validation on a Nationwide Cohort

Valliani, A. A., Kim, N. C., Martini, M. L., Gal, J. S., Neifert, S. N., Feng, R., Geng, E. A., Kim, J. S., Cho, S. K., Oermann, E. K., et al. (2022) · World Neurosurgery

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 21

Towards Improving Faithfulness in Abstractive Summarization

Chen, X., Li, M., Gao, X., & Zhang, X. (2022) · Advances in Neural Information Processing Systems 35

Topic ModelingAdvanced Text Analysis Techniques

Cited by 21

Indigenous Data Sovereignty: A Catalyst for Ethical AI in Business

Rana, V. (2025) · Business & Society

Ethics and Social Impacts of AIIndigenous Health, Education, and Rights

Cited by 21

A Framework for Automatic Text Generation of Trends in Physiological Time Series Data

Banaee, H., Ahmed, M. U., & Loutfi, A. (2013) · 2013 IEEE International Conference on Systems, Man, and Cybernetics

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 21

Learning to Model Editing Processes

Reid, M., & Neubig, G. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 21

Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generation

Yuan, X., Wang, T., Wang, Y.-H., Fine, E., Abdelghani, R., Sauzéon, H., & Oudeyer, P.-Y. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Topic ModelingNatural Language Processing Techniques

Cited by 21

Natural language generation for sponsored-search advertisements

Bartz, K., Barr, C., & Aijaz, A. (2008) · Proceedings of the 9th ACM conference on Electronic commerce

Natural Language Processing TechniquesInformation Retrieval and Search Behavior

Cited by 21

Moving Virtual Reality out of its Comfort Zone and Into the African Kalahari Desert Field: Experiences From Technological Co-Exploration With an Indigenous San Community in Namibia

Rodil, K., Maasz, D., & Winschiers-Theophilus, H. (2020) · 26th ACM Symposium on Virtual Reality Software and Technology

ICT in Developing CommunitiesVirtual Reality Applications and Impacts

Cited by 21

Towards Safety and Sustainability: Designing Local Recommendations for Post-pandemic World

Patro, G. K., Chakraborty, A., Banerjee, A., & Ganguly, N. (2020) · Fourteenth ACM Conference on Recommender Systems

Recommender Systems and TechniquesGame Theory and Voting Systems

Cited by 21

Pseudo Constant Time Implementations of TLS Are Only Pseudo Secure

Ronen, E., Paterson, K. G., & Shamir, A. (2018) · Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security

Cryptographic Implementations and SecuritySecurity and Verification in Computing

Cited by 21

Analysis of sentence embedding models using prediction tasks in natural language processing

Adi, Y., Kermany, E., Belinkov, Y., Lavi, O., & Goldberg, Y. (2017) · IBM Journal of Research and Development

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 21

Rome was built in 1776: A Case Study on Factual Correctness in Knowledge-Grounded Response Generation

Santhanam, S., Hedayatnia, B., Gella, S., Padmakumar, A., Kim, S., Liu, Y., & Hakkani-Tur, D. (2021) · arXiv

Topic ModelingSpeech and dialogue systems

Cited by 21

Cluster state preparation using gates operating at arbitrary success probabilities

Kieling, K., Gross, D., & Eisert, J. (2007) · New Journal of Physics

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 21

Accelerating Parkinson’s Disease drug development with federated learning approaches

Khanna, A., Adams, J., Antoniades, C., Bloem, B. R., Carroll, C., Cedarbaum, J., Cosman, J., Dexter, D. T., Dockendorf, M. F., Edgerton, J., et al. (2024) · npj Parkinson's Disease

Privacy-Preserving Technologies in DataParkinson's Disease Mechanisms and Treatments

Cited by 21

A Unified Sequence-to-Sequence Front-End Model for Mandarin Text-to-Speech Synthesis

Pan, J., Yin, X., Zhang, Z., Liu, S., Zhang, Y., Ma, Z., & Wang, Y. (2020) · ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 21

Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulation

Schmalstieg, F., Honerkamp, D., Welschehold, T., & Valada, A. (2023) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 21

Typing Exercises as Interactive Worked Examples for Deliberate Practice in CS Courses

Gaweda, A. M., Lynch, C. F., Seamon, N., Silva de Oliveira, G., & Deliwa, A. (2020) · Proceedings of the Twenty-Second Australasian Computing Education Conference

Teaching and Learning ProgrammingIntelligent Tutoring Systems and Adaptive Learning

Cited by 21

Data Statements: From Technical Concept to Community Practice

McMillan-Major, A., Bender, E. M., & Friedman, B. (2024) · ACM Journal on Responsible Computing

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 21

Meta-Sim: Learning to Generate Synthetic Datasets

Kar, A., Prakash, A., Liu, M.-Y., Cameracci, E., Yuan, J., Rusiniak, M., Acuna, D., Torralba, A., & Fidler, S. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisComputer Graphics and Visualization Techniques

Cited by 21

Explainable LSTM Model for Anomaly Detection in HDFS Log File using Layerwise Relevance Propagation

Patil, A., Wadekar, A., Gupta, T., Vijan, R., & Kazi, F. (2019) · 2019 IEEE Bombay Section Signature Conference (IBSSC)

Software System Performance and ReliabilityExplainable Artificial Intelligence (XAI)

Cited by 21

Towards building an attentive artificial listener: on the perception of attentiveness in audio-visual feedback tokens,

Oertel, C., Lopes, J., Yu, Y., Mora, K. A. F., Gustafson, J., Black, A. W., & Odobez, J.-M. (2016) · Proceedings of the 18th ACM International Conference on Multimodal Interaction

Speech and dialogue systemsSocial Robot Interaction and HRI

Cited by 21