| Secrets of rlhf in large language models part i: Ppo R Zheng, S Dou, S Gao, Y Hua, W Shen, B Wang, Y Liu, S Jin, Q Liu, ... arXiv preprint arXiv:2307.04964, 2023 | 29 | 2023 |
| Zhiheng Xi R Zheng, S Dou, S Gao, Y Hua, W Shen, B Wang, Y Liu, S Jin, Q Liu, ... Nuo Xu, Wenbin Lai, Minghao Zhu, Cheng Chang, Zhangyue Yin, Rongxiang Weng …, 2023 | 20 | 2023 |
| Self-polish: Enhance reasoning in large language models via problem refinement Z Xi, S Jin, Y Zhou, R Zheng, S Gao, T Gui, Q Zhang, X Huang arXiv preprint arXiv:2305.14497, 2023 | 14 | 2023 |
| Secrets of rlhf in large language models part ii: Reward modeling B Wang, R Zheng, L Chen, Y Liu, S Dou, C Huang, W Shen, S Jin, E Zhou, ... arXiv preprint arXiv:2401.06080, 2024 | 9 | 2024 |
| Loramoe: Revolutionizing mixture of experts for maintaining world knowledge in language model alignment S Dou, E Zhou, Y Liu, S Gao, J Zhao, W Shen, Y Zhou, Z Xi, X Wang, ... arXiv preprint arXiv:2312.09979, 2023 | 7 | 2023 |
| Kernel-whitening: Overcome dataset bias with isotropic sentence embedding S Gao, S Dou, Q Zhang, X Huang arXiv preprint arXiv:2210.07547, 2022 | 6 | 2022 |
| Decorrelate irrelevant, purify relevant: Overcome textual spurious correlations from a feature perspective S Dou, R Zheng, T Wu, S Gao, J Shan, Q Zhang, Y Wu, X Huang arXiv preprint arXiv:2202.08048, 2022 | 5 | 2022 |
| Zhiheng Xi, Rui Zheng, Yicheng Zou, Tao Gui, et al. 2023b. Trace: A comprehensive benchmark for continual learning in large language models X Wang, Y Zhang, T Chen, S Gao, S Jin, X Yang arXiv preprint arXiv:2310.06762, 0 | 5 | |
| Zhiheng Xi, Xiao Wang, Xiaoran Fan, Shiliang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, and Xuanjing Huang. 2023 S Dou, E Zhou, Y Liu, S Gao, J Zhao, W Shen, Y Zhou Loramoe: Revolutionizing mixture of experts for maintaining world knowledge …, 0 | 5 | |
| Zhiheng Xi B Wang, R Zheng, L Chen, Y Liu, S Dou, C Huang, W Shen, S Jin, E Zhou, ... Jun Zhao, Xiao Wang, Tao Ji, Hang Yan, Lixing Shen, Zhan Chen, Tao Gui, Qi …, 2024 | 4 | 2024 |
| Farewell to aimless large-scale pretraining: Influential subset selection for language model X Wang, W Zhou, Q Zhang, J Zhou, S Gao, J Wang, M Zhang, X Gao, ... arXiv preprint arXiv:2305.12816, 2023 | 4 | 2023 |
| Tooleyes: Fine-grained evaluation for tool learning capabilities of large language models in real-world scenarios J Ye, G Li, S Gao, C Huang, Y Wu, S Li, X Fan, S Dou, Q Zhang, T Gui, ... arXiv preprint arXiv:2401.00741, 2024 | 3 | 2024 |
| Navigating the OverKill in Large Language Models C Shi, X Wang, Q Ge, S Gao, X Yang, T Gui, Q Zhang, X Huang, X Zhao, ... arXiv preprint arXiv:2401.17633, 2024 | 2 | 2024 |
| Delve into ppo: Implementation matters for stable rlhf R Zheng, S Dou, S Gao, Y Hua, W Shen, B Wang, Y Liu, S Jin, Y Zhou, ... NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following, 2023 | 2 | 2023 |
| On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection S Gao, S Dou, Q Zhang, X Huang, J Ma, Y Shan arXiv preprint arXiv:2306.15705, 2023 | 2 | 2023 |
| DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization S Gao, S Dou, Y Liu, X Wang, Q Zhang, Z Wei, J Ma, Y Shan arXiv preprint arXiv:2306.15164, 2023 | 2 | 2023 |
| ToolSword: Unveiling Safety Issues of Large Language Models in Tool Learning Across Three Stages J Ye, S Li, G Li, C Huang, S Gao, Y Wu, Q Zhang, T Gui, X Huang arXiv preprint arXiv:2402.10753, 2024 | 1 | 2024 |
| Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback S Gao, Q Ge, W Shen, S Dou, J Ye, X Wang, R Zheng, Y Zou, Z Chen, ... arXiv preprint arXiv:2401.11458, 2024 | 1 | 2024 |
| Trace: A comprehensive benchmark for continual learning in large language models X Wang, Y Zhang, T Chen, S Gao, S Jin, X Yang, Z Xi, R Zheng, Y Zou, ... arXiv preprint arXiv:2310.06762, 2023 | 1 | 2023 |
| CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing S Gao, S Dou, J Shan, Q Zhang, X Huang arXiv preprint arXiv:2305.02865, 2023 | 1 | 2023 |
