| Raft: Reward ranked finetuning for generative foundation model alignment H Dong, W Xiong, D Goyal, Y Zhang, W Chow, R Pan, S Diao, J Zhang, ... Transactions on Machine Learning Research (TMLR), 2023 | 123 | 2023 |
| Weakly supervised disentangled generative causal representation learning X Shen, F Liu, H Dong, Q Lian, Z Chen, T Zhang Journal of Machine Learning Research 23 (241), 1-55, 2022 | 93* | 2022 |
| Local augmentation for graph neural networks S Liu, R Ying, H Dong, L Li, T Xu, Y Rong, P Zhao, J Huang, D Wu International conference on machine learning, 14054-14072, 2022 | 84 | 2022 |
| Bayesian invariant risk minimization Y Lin, H Dong, H Wang, T Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 56 | 2022 |
| DetGPT: Detect What You Need via Reasoning R Pi, J Gao, S Diao, R Pan, H Dong, J Zhang, L Yao, J Han, H Xu, ... Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 45* | 2023 |
| Lmflow: An extensible toolkit for finetuning and inference of large foundation models S Diao, R Pan, H Dong, KS Shum, J Zhang, W Xiong, T Zhang Annual Conference of the North American Chapter of the Association for …, 2024 | 36 | 2024 |
| Mathematical models of overparameterized neural networks C Fang, H Dong, T Zhang Proceedings of the IEEE 109 (5), 683-703, 2021 | 28 | 2021 |
| Higher-order weighted graph convolutional networks S Liu, L Chen, H Dong, Z Wang, D Wu, Z Huang arXiv preprint arXiv:1911.04129, 2019 | 25 | 2019 |
| Vocabulary-informed Zero-shot and Open-set Learning Y Fu, X Wang, H Dong, YG Jiang, M Wang, X Xue, L Sigal IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 | 20 | 2019 |
| Over parameterized two-level neural networks can learn near optimal feature representations C Fang, H Dong, T Zhang arXiv preprint arXiv:1910.11508, 2019 | 16 | 2019 |
| Learning the Compositional Domains for Generalized Zero-shot Learning H Dong, Y Fu, SJ Hwang, L Sigal, X Xue Computer Vision and Image Understanding, 103454, 2022 | 12* | 2022 |
| MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance R Pi, T Han, Y Xie, R Pan, Q Lian, H Dong, J Zhang, T Zhang arXiv preprint arXiv:2401.02906, 2024 | 10 | 2024 |
| Gibbs sampling from human feedback: A provable kl-constrained framework for rlhf W Xiong, H Dong, C Ye, H Zhong, N Jiang, T Zhang arXiv preprint arXiv:2312.11456, 2023 | 10 | 2023 |
| Reverse Diffusion Monte Carlo X Huang, H Dong, HAO Yifan, Y Ma, T Zhang The Twelfth International Conference on Learning Representations, 2023 | 8* | 2023 |
| Particle-based variational inference with preconditioned functional gradient flow H Dong, X Wang, Y Lin, T Zhang The Eleventh International Conference on Learning Representations, 2023 | 8 | 2023 |
| Spurious feature diversification improves out-of-distribution generalization Y Lin, L Tan, Y Hao, H Wong, H Dong, W Zhang, Y Yang, T Zhang arXiv preprint arXiv:2309.17230, 2023 | 7 | 2023 |
| Error compensated loopless svrg, quartz, and sdca for distributed optimization X Qian, H Dong, P Richtárik, T Zhang arXiv preprint arXiv:2109.10049, 2021 | 5 | 2021 |
| Extreme vocabulary learning H Dong, Z Sun, Y Fu, S Zhong, Z Zhang, YG Jiang Frontiers of Computer Science 14 (6), 1-12, 2019 | 5* | 2019 |
| Error Compensated Loopless SVRG for Distributed Optimization X Qian, H Dong, P Richtárik, T Zhang OPT2020: 12th Annual Workshop on Optimization for Machine Learning (NeurIPS …, 2020 | 3 | 2020 |
| Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo X Huang, D Zou, H Dong, Y Ma, T Zhang arXiv preprint arXiv:2401.06325, 2024 | 2 | 2024 |
Tong ZhangHKUSTVerified email at tongzhang-ml.org
