no code implementations • ICML 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Generative adversarial imitation learning (GAIL) demonstrates tremendous success in practice, especially when combined with neural networks.
no code implementations • 23 Apr 2024 • Yufeng Zhang, Xuepeng Wang, Lingxiang Wu, Jinqiao Wang
In this paper, we propose Pattern-Aware CoT, a prompting method that considers the diversity of demonstration patterns.
no code implementations • 18 Apr 2024 • Yuchen Zhu, Yufeng Zhang, Zhaoran Wang, Zhuoran Yang, Xiaohong Chen
Under this regime, gradient descent-ascent corresponds to a Wasserstein gradient flow over the space of probability measures defined over the space of neural network parameters.
no code implementations • 15 Apr 2024 • Cheng Jiang, Alexander Gedeon, Yiwei Lyu, Eric Landgraf, Yufeng Zhang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Honglak Lee, Todd Hollon
Volumetric biomedical microscopy has the potential to increase the diagnostic information extracted from clinical tissue specimens and improve the diagnostic accuracy of both human pathologists and computational pathology models.
no code implementations • 11 Mar 2024 • Yufeng Zhang, Liyu Chen, Boyi Liu, Yingxiang Yang, Qiwen Cui, Yunzhe Tao, Hongxia Yang
Recent advances in reinforcement learning (RL) algorithms aim to enhance the performance of language models at scale.
no code implementations • 8 Mar 2024 • Hongyi Guo, Zhihan Liu, Yufeng Zhang, Zhaoran Wang
Large Language Models (LLMs) harness extensive data from the Internet, storing a broad spectrum of prior knowledge.
no code implementations • 1 Feb 2024 • Qilong Yan, Yufeng Zhang, Jinghao Zhang, Jingpu Duan, Jian Yin
This could lead the meta-learner to face complex tasks too soon, hindering proper learning.
no code implementations • 12 Sep 2023 • Yufeng Zhang, Meng-xiang Wang, Jianxing Yu
We first retrieve all answer-related clues from multiple knowledge sources on facts and opinions.
no code implementations • 29 Aug 2023 • Lei Han, Qingxu Zhu, Jiapeng Sheng, Chong Zhang, Tingguang Li, Yizheng Zhang, He Zhang, Yuzhen Liu, Cheng Zhou, Rui Zhao, Jie Li, Yufeng Zhang, Rui Wang, Wanchao Chi, Xiong Li, Yonghui Zhu, Lingzhu Xiang, Xiao Teng, Zhengyou Zhang
In this work, we propose a framework for driving legged robots act like real animals with lifelike agility and strategy in complex environments.
no code implementations • 7 Jun 2023 • Martin H. Nielsen, Yufeng Zhang, Changbin Xue, Jian Ren, Yingzeng Yin, Ming Shen, Gert F. Pedersen
One key communication block in 5G and 6G radios is the active phased array (APA).
no code implementations • 30 May 2023 • Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang, Zhaoran Wang
(b) What is a proper performance metric for ICL and what is the error rate?
no code implementations • 30 Dec 2022 • Yufeng Zhang, Boyi Liu, Qi Cai, Lingxiao Wang, Zhaoran Wang
In particular, such a representation instantiates the posterior distribution of the latent variable given input tokens, which plays a central role in predicting output labels and solving downstream tasks.
no code implementations • 20 Oct 2022 • Zheng Li, Caili Guo, Zerun Feng, Jenq-Neng Hwang, Ying Jin, Yufeng Zhang
Such a binary indicator covers only a limited subset of image-text semantic relations, which is insufficient to represent relevance degrees between images and texts described by continuous labels such as image captions.
1 code implementation • 3 Sep 2022 • Yufeng Zhang, Weiqing Wang, Hongzhi Yin, Pengpeng Zhao, Wei Chen, Lei Zhao
A more challenging scenario is that emerging KGs consist of only unseen entities, called as disconnected emerging KGs (DEKGs).
no code implementations • 11 Jun 2022 • Doudou Zhou, Yufeng Zhang, Aaron Sonabend-W, Zhaoran Wang, Junwei Lu, Tianxi Cai
Extensive simulations demonstrate the effectiveness of the proposed algorithm.
no code implementations • NeurIPS 2021 • Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang
Specifically, we consider a version of AC where the actor and critic are represented by overparameterized two-layer neural networks and are updated with two-timescale learning rates.
no code implementations • NeurIPS 2021 • Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
In constrained multi-objective RL, the goal is to learn a policy that achieves the best performance specified by a multi-objective preference function under a constraint.
Multi-Objective Reinforcement Learning reinforcement-learning
1 code implementation • 14 Oct 2021 • Qilong Yan, Yufeng Zhang, Qiang Liu, Shu Wu, Liang Wang
User profiling has long been an important problem that investigates user interests in many real applications.
no code implementations • 19 Aug 2021 • Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
In generative adversarial imitation learning (GAIL), the agent aims to learn a policy from an expert demonstration so that its performance cannot be discriminated from the expert policy on a certain predefined reward set.
no code implementations • 15 Aug 2021 • Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu
To train high-performing models with the minimal annotation cost, active learning is proposed to select and label the most informative samples, yet it is still challenging to measure informativeness of samples used in DNNs.
no code implementations • 8 Mar 2021 • Yi Wang, Jinxiang Yao, Yufeng Zhang
For C1-smooth strongly monotone discrete-time dynamical systems, it is shown that ``convergence to linearly stable cycles" is a prevalent asymptotic behavior in the measuretheoretic sense.
Dynamical Systems
1 code implementation • 28 Jan 2021 • Yufeng Zhang, Jinghao Zhang, Zeyu Cui, Shu Wu, Liang Wang
To retrieve more relevant, appropriate and useful documents given a query, finding clues about that query through the text is crucial.
no code implementations • 18 Jan 2021 • Xiangzhuo Xing, Yue Sun, Xiaolei Yi, Meng Li, Jiajia Feng, Yan Meng, Yufeng Zhang, Wenchong Li, Nan Zhou, Xiude He, Jun-Yi Ge, Wei Zhou, Tsuyoshi Tamegai, Zhixiang Shi
FeSe$_{1-x}$Te$_{x}$ superconductors manifest some intriguing electronic properties depending on the value of $x$.
Superconductivity Materials Science
no code implementations • 1 Jan 2021 • Yufeng Zhang, Yunan Zhang, ChengXiang Zhai
To classify images, neural networks extract features from raw inputs and then sum them up with fixed weights via the fully connected layer.
no code implementations • 21 Dec 2020 • Zhuoran Yang, Yufeng Zhang, Yongxin Chen, Zhaoran Wang
Specifically, we prove that moving along the geodesic in the direction of functional gradient with respect to the second-order Wasserstein distance is equivalent to applying a pushforward mapping to a probability distribution, which can be approximated accurately by pushing a set of particles.
no code implementations • NeurIPS 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang
Temporal-difference and Q-learning play a key role in deep reinforcement learning, where they are empowered by expressive nonlinear function approximators such as neural networks.
no code implementations • 8 Jun 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang
We aim to answer the following questions: When the function approximator is a neural network, how does the associated feature representation evolve?
1 code implementation • ACL 2020 • Yufeng Zhang, Xueli Yu, Zeyu Cui, Shu Wu, Zhongzhen Wen, Liang Wang
We first build individual graphs for each document and then use GNN to learn the fine-grained word representations based on their local structures, which can also effectively produce embeddings for unseen words in the new document.
no code implementations • 8 Mar 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Generative adversarial imitation learning (GAIL) demonstrates tremendous success in practice, especially when combined with neural networks.
no code implementations • 9 Feb 2020 • Yufeng Zhang, Jialu Pan, Wanwei Liu, Zhenbang Chen, Ji Wang, Zhiming Liu, Kenli Li, Hongmei Wei
For point-wise anomaly detection, our method achieves 90. 7\% AUROC on average and outperforms the baseline by 5. 2\% AUROC.
no code implementations • 11 Nov 2019 • Yunan Zhang, Xiang Cheng, Yufeng Zhang, Zihan Wang, Zhengqi Fang, Xiaoyan Wang, Zhenya Huang, ChengXiang Zhai
Answering complex questions involving multiple entities and relations is a challenging task.
1 code implementation • 11 Apr 2019 • Hao Wu, Jiayuan Mao, Yufeng Zhang, Yuning Jiang, Lei LI, Weiwei Sun, Wei-Ying Ma
We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a joint space of visual and textual concepts.