Niebles, Juan Carlos

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

ActivityNet: A large-scale video benchmark for human activity understanding

Heilbron, F. C., Escorcia, V., Ghanem, B., & Niebles, J. C. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionContext-Aware Activity Recognition Systems

Cited by 2,578

Spatio-Temporal Graph for Video Captioning With Knowledge Distillation

Pan, B., Cai, H., Huang, D.-A., Lee, K.-H., Gaidon, A., Adeli, E., & Niebles, J. C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 281

End-to-End, Single-Stream Temporal Action Detection in Untrimmed Videos

Buch, S., Escorcia, V., Ghanem, B., & Niebles, J. C. (2017) · Procedings of the British Machine Vision Conference 2017

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 240

Connectionist Temporal Modeling for Weakly Supervised Action Labeling

Huang, D.-A., Fei-Fei, L., & Niebles, J. C. (2016) · Lecture Notes in Computer Science

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 226

Artificial Intelligence Index Report 2024

Maslej, N., Fattorini, L., Perrault, R., Parli, V., Reuel, A., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., et al. (2024) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 159

The AI Index 2022 Annual Report

Zhang, D., Maslej, N., Brynjolfsson, E., Etchemendy, J., Lyons, T., Manyika, J., Ngo, H., Niebles, J. C., Sellitto, M., Sakhaee, E., et al. (2022) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 146

ULIP-2: Towards Scalable Multimodal Pre-Training for 3D Understanding

Xue, L., Yu, N., Zhang, S., Panagopoulou, A., Li, J., Martín-Martín, R., Wu, J., Xiong, C., Xu, R., Niebles, J. C., et al. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisMultimodal Machine Learning Applications

Cited by 144

Graph Distillation for Action Detection with Privileged Modalities

Luo, Z., Hsieh, J.-T., Jiang, L., Niebles, J. C., & Fei-Fei, L. (2018) · Lecture Notes in Computer Science

Human Pose and Action RecognitionDomain Adaptation and Few-Shot Learning

Cited by 111

Learning Privacy-preserving Optics for Human Pose Estimation

Hinojosa, C., Niebles, J. C., & Arguello, H. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Privacy-Preserving Technologies in DataAdvanced Neural Network Applications

Cited by 62

Artificial Intelligence Index Report 2025

Maslej, N., Fattorini, L., Perrault, R., Gil, Y., Parli, V., Kariuki, N., Capstick, E., Reuel, A., Brynjolfsson, E., Etchemendy, J., et al. (2025) · arXiv

Artificial Intelligence ApplicationsEthics and Social Impacts of AI

Cited by 50

The AI Index 2021 Annual Report

Zhang, D., Mishra, S., Brynjolfsson, E., Etchemendy, J., Ganguli, D., Grosz, B., Lyons, T., Manyika, J., Niebles, J. C., Sellitto, M., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 48

Apigen: Automated pipeline for generating verifiable and diverse function-calling datasets

Liu, Z., Hoang, T., Zhang, J., Zhu, M., Lan, T., Kokane, S., Tan, J., Yao, W., Liu, Z., Feng, Y., et al. (2024) · Advances in Neural Information Processing Systems 37

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 13

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets

Liu, Z., Hoang, T., Zhang, J., Zhu, M., Lan, T., Kokane, S., Tan, J., Yao, W., Liu, Z., Feng, Y., et al. (2024) · arXiv

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 13

BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

Liu, Z., Yao, W., Zhang, J., Xue, L., Heinecke, S., Murthy, R., Feng, Y., Chen, Z., Niebles, J. C., Arpit, D., et al. (2023) · arXiv

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 11

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

Yao, W., Heinecke, S., Niebles, J. C., Liu, Z., Feng, Y., Xue, L., Murthy, R., Chen, Z., Zhang, J., Arpit, D., et al. (2023) · arXiv

Reinforcement Learning in RoboticsNatural Language Processing Techniques

Cited by 10

APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay

Prabhakar, A., Liu, Z., Zhu, M., Zhang, J., Awalgaonkar, T., Wang, S., Liu, Z., Chen, H., Hoang, T., Niebles, J. C., et al. (2025) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 2