no code implementations • 19 Feb 2024 • Qisen Yang, Zekun Wang, Honghui Chen, Shenzhi Wang, Yifan Pu, Xin Gao, Wenhao Huang, Shiji Song, Gao Huang
Psychological measurement is essential for mental health, self-understanding, and personal development.
1 code implementation • NeurIPS 2023 • Shenzhi Wang, Qisen Yang, Jiawei Gao, Matthieu Gaetan Lin, Hao Chen, Liwei Wu, Ning Jia, Shiji Song, Gao Huang
Existing solutions tackle this problem by imposing a policy constraint on the policy improvement objective in both offline and online learning.
no code implementations • 2 Oct 2023 • Shenzhi Wang, Chang Liu, Zilong Zheng, Siyuan Qi, Shuo Chen, Qisen Yang, Andrew Zhao, Chaofei Wang, Shiji Song, Gao Huang
This study utilizes the intricate Avalon game as a testbed to explore LLMs' potential in deceptive environments.
no code implementations • 4 Sep 2023 • Qisen Yang, Shenzhi Wang, Qihang Zhang, Gao Huang, Shiji Song
Offline reinforcement learning (RL) optimizes the policy on a previously collected dataset without any interactions with the environment, yet usually suffers from the distributional shift problem.
2 code implementations • 8 Jun 2023 • Yang Yue, Bingyi Kang, Xiao Ma, Qisen Yang, Gao Huang, Shiji Song, Shuicheng Yan
OPER is a plug-and-play component for offline RL algorithms.
no code implementations • 6 Jun 2023 • Qisen Yang, Shenzhi Wang, Matthieu Gaetan Lin, Shiji Song, Gao Huang
In particular, online fine-tuning has become a commonly used method to correct the erroneous estimates of out-of-distribution data learned in the offline training phase.
1 code implementation • 12 Oct 2022 • Chaofei Wang, Qisen Yang, Rui Huang, Shiji Song, Gao Huang
Knowledge distillation is an effective approach to learn compact models (students) with the supervision of large and strong models (teachers).
no code implementations • 13 Sep 2021 • Chaofei Wang, Shiji Song, Qisen Yang, Xiang Li, Gao Huang
As a data augmentation method, FOT can be conveniently applied to any existing few shot learning algorithm and greatly improve its performance on FG-FSL tasks.
no code implementations • ICCV 2021 • Chaofei Wang, Jiayu Xiao, Yizeng Han, Qisen Yang, Shiji Song, Gao Huang
The backbone of traditional CNN classifier is generally considered as a feature extractor, followed by a linear layer which performs the classification.