| Bias and fairness in large language models: A survey IO Gallegos, RA Rossi, J Barrow, MM Tanjim, S Kim, F Dernoncourt, T Yu, ... Computational Linguistics, 1-79, 2024 | 363 | 2024 |
| Towards Language-Free Training for Text-to-Image Generation Y Zhou, R Zhang, C Chen, C Li, C Tensmeyer, T Yu, J Gu, J Xu, T Sun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 283 | 2022 |
| Understanding and improving recurrent networks for human activity recognition by continuous attention M Zeng, H Gao, T Yu, OJ Mengshoel, H Langseth, I Lane, X Liu Proceedings of the 2018 ACM International Symposium on Wearable Computers, 56-63, 2018 | 197 | 2018 |
| Footprintid: Indoor pedestrian identification through ambient structural vibration sensing S Pan, T Yu, M Mirshekari, J Fagert, A Bonde, OJ Mengshoel, HY Noh, ... Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2017 | 177 | 2017 |
| Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning R Zhang, T Yu, Y Shen, H Jin, C Chen Advances in Neural Information Processing Systems, 15214-15224, 2019 | 166* | 2019 |
| Big data small footprint: The design of a low-power classifier for detecting transportation modes MC Yu, T Yu, SC Wang, CJ Lin, EY Chang Proceedings of the VLDB Endowment 7 (13), 1429-1440, 2014 | 142 | 2014 |
| Towards building the federatedGPT: Federated instruction tuning J Zhang, S Vahidian, M Kuo, C Li, R Zhang, T Yu, G Wang, Y Chen ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 107 | 2024 |
| Uncovering the disentanglement capability in text-to-image diffusion models Q Wu, Y Liu, H Zhao, A Kale, T Bui, T Yu, Z Lin, Y Zhang, S Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 96 | 2023 |
| Semi-supervised convolutional neural networks for human activity recognition M Zeng, T Yu, X Wang, LT Nguyen, OJ Mengshoel, I Lane Big Data (Big Data), 2017 IEEE International Conference on, 522-529, 2017 | 90 | 2017 |
| A Visual Dialog Augmented Interactive Recommender System T Yu, Y Shen, H Jin Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 76 | 2019 |
| EI-CLIP: Entity-Aware Interventional Contrastive Learning for E-Commerce Cross-Modal Retrieval H Ma, H Zhao, Z Lin, A Kale, Z Wang, T Yu, J Gu, S Choudhary, X Xie Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 65 | 2022 |
| Large language models and causal inference in collaboration: A comprehensive survey X Liu, P Xu, J Wu, J Yuan, Y Yang, Y Zhou, F Liu, T Guan, H Wang, T Yu, ... arXiv preprint arXiv:2403.09606, 2024 | 51 | 2024 |
| Comparison-based Conversational Recommender System with Relative Bandit Feedback Z Xie, T Yu, C Zhao, S Li Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 44 | 2021 |
| Effective string processing and matching for author disambiguation WS Chin, YC Juan, Y Zhuang, F Wu, HY Tung, T Yu, JP Wang, CX Chang, ... Proceedings of the 2013 KDD Cup 2013 workshop, 1-9, 2013 | 44 | 2013 |
| Figure Captioning with Reasoning and Sequence-Level Training C Chen, R Zhang, E Koh, S Kim, S Cohen, T Yu, R Rossi, R Bunescu arXiv preprint arXiv:1906.02850, 2019 | 43 | 2019 |
| Customized nonlinear bandits for online response selection in neural conversation models B Liu, T Yu, I Lane, OJ Mengshoel Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 43 | 2018 |
| QoS-Aware Scheduling of Heterogeneous Servers for Inference in Deep Neural Networks Z Fang, T Yu, OJ Mengshoel, RK Gupta Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 40 | 2017 |
| Vision-Language Recommendation via Attribute Augmented Multimodal Reinforcement Learning T Yu, Y Shen, R Zhang, X Zeng, H Jin Proceedings of the 27th ACM International Conference on Multimedia, 39-47, 2019 | 39 | 2019 |
| Improving Demand Prediction in Bike Sharing System by Learning Global Features M Zeng, T Yu, X Wang, V Su, LT Nguyen, OJ Mengshoel Machine Learning for Large Scale Transportation Systems (LSTS)@ KDD-16, 2016 | 39 | 2016 |
| The closeness of in-context learning and weight shifting for softmax regression S Li, Z Song, Y Xia, T Yu, T Zhou arXiv preprint arXiv:2304.13276, 2023 | 37 | 2023 |
Ruiyi ZhangAdobe ResearchVerified email at cs.duke.edu
