1 code implementation • 18 Apr 2024 • Jingmin Sun, Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
More importantly, we provide three extrapolation studies to demonstrate that PROSE-PDE can generalize physical features through the robust training of multiple operators and that the proposed model can extrapolate to predict PDE solutions whose models or data were unseen during the training.
no code implementations • 10 Apr 2024 • Fulong Ma, Weiqing Qi, Guoyang Zhao, Linwei Zheng, Sheng Wang, Yuxuan Liu, Ming Liu
This review looks back and analyzes the current state of achievements in the field of 3D lane detection research.
no code implementations • 28 Mar 2024 • Jiaxing Chen, Yuxuan Liu, Dehu Li, Xiang An, Ziyong Feng, Yongle Zhao, Yin Xie
The surge of Multimodal Large Language Models (MLLMs), given their prominent emergent capabilities in instruction following and reasoning, has greatly advanced the field of visual reasoning.
1 code implementation • 25 Mar 2024 • Guoyang Zhao, Fulong Ma, Yuxuan Liu, Weiqing Qi, Ming Liu
Moreover, we propose an adaptive weighted loss function group, specifically formulated to counteract the imbalance in the distribution of curb point clouds relative to other categories.
no code implementations • 12 Mar 2024 • Yi Zeng, Zhengning Wang, Yuxuan Liu, Tianjiao Zeng, Xuhang Liu, Xinglong Luo, Shuaicheng Liu, Shuyuan Zhu, Bing Zeng
Since texture details intertwine with compression artifacts in compressed dark images, detail enhancement and blocking artifacts suppression contradict each other in image space.
no code implementations • 8 Mar 2024 • Hongda Sun, Yuxuan Liu, ChengWei Wu, Haiyu Yan, Cheng Tai, Xin Gao, Shuo Shang, Rui Yan
Open-domain question answering (ODQA) has emerged as a pivotal research spotlight in information systems.
1 code implementation • 4 Mar 2024 • Yuxuan Liu
Collectively, these contributions lay a robust foundation for the widespread adoption of vision-based 3D perception technologies in autonomous driving applications.
no code implementations • 24 Feb 2024 • Yuxuan Liu, Tianchi Yang, Shaohan Huang, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang
Large language models (LLMs) have emerged as a promising alternative to expensive human evaluations.
no code implementations • 19 Feb 2024 • Yuxuan Liu, Tianchi Yang, Shaohan Huang, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang
Diffusion models have demonstrated exceptional capability in generating high-quality images, videos, and audio.
no code implementations • 4 Jan 2024 • Yuxuan Liu, Haozhao Wang, Shuang Wang, Zhiming He, Wenchao Xu, Jialiang Zhu, Fan Yang
Estimating causal effects among different events is of great importance to critical fields such as drug development.
1 code implementation • 20 Oct 2023 • Zhaoyang Wang, Shaohan Huang, Yuxuan Liu, Jiahai Wang, Minghui Song, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang
In this paper, we propose a tailored learning approach to distill such reasoning ability to smaller LMs to facilitate the democratization of the exclusive reasoning ability.
no code implementations • 2 Oct 2023 • Fulong Ma, Xiaoyang Yan, Guoyang Zhao, Xiaojie Xu, Yuxuan Liu, Ming Liu
Monocular 3D object detection plays a crucial role in autonomous driving.
1 code implementation • 28 Sep 2023 • Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
Approximating nonlinear differential equations using a neural network provides a robust and efficient tool for various scientific computing tasks, including real-time predictions, inverse problems, optimal controls, and surrogate modeling.
no code implementations • 23 Sep 2023 • Yuxuan Liu, Tianchi Yang, Shaohan Huang, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang
Recent advancements in large language models (LLMs) on language modeling and emergent capabilities make them a promising reference-free evaluator of natural language generation quality, and a competent alternative to human evaluation.
no code implementations • 10 May 2023 • Yuxuan Liu, Xi Chen, Pieter Abbeel
Leveraging this insight, we learn a grasp segmentation model to segment the grasped object from before and after grasp images.
no code implementations • 3 May 2023 • Yuxuan Liu, Nikhil Mishra, Pieter Abbeel, Xi Chen
Existing state-of-the-art methods are often unable to capture meaningful uncertainty in challenging or ambiguous scenes, and as such can cause critical errors in high-performance applications.
no code implementations • 21 Apr 2023 • Yuxuan Liu, Zhenhua Xu, Huaiyang Huang, Lujia Wang, Ming Liu
Predicting accurate depth with monocular images is important for low-cost robotic applications and autonomous driving.
1 code implementation • 28 Feb 2023 • Zhongli Fan, Li Zhang, Yuxuan Liu
We present an effective method for the matching of multimodal images.
1 code implementation • 11 Dec 2022 • Yuxuan Liu, Scott G. McCalla, Hayden Schaeffer
Particle dynamics and multi-agent systems provide accurate dynamical models for studying and forecasting the behavior of complex interacting systems.
no code implementations • 13 Oct 2022 • Yuxuan Liu, Nikhil Mishra, Maximilian Sieb, Yide Shentu, Pieter Abbeel, Xi Chen
3D bounding boxes are a widespread intermediate representation in many computer vision applications.
no code implementations • 21 Sep 2022 • Zhenhua Xu, Yuxuan Liu, Yuxiang Sun, Ming Liu, Lujia Wang
To annotate road network graphs effectively and efficiently, automatic algorithms for road network graph detection are demanded.
no code implementations • 16 Sep 2022 • Zhenhua Xu, Yuxuan Liu, Yuxiang Sun, Ming Liu, Lujia Wang
Due to the use of the DETR-like transformer network, CenterLineDet can handle complicated graph topology, such as lane intersections.
1 code implementation • 23 Aug 2022 • Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu
The advent of the big data era brought new opportunities and challenges to draw treatment effect in data fusion, that is, a mixed dataset collected from multiple sources (each source with an independent treatment assignment mechanism).
1 code implementation • 20 Jul 2022 • Xiao Gu, Yao Guo, Zeju Li, Jianing Qiu, Qi Dou, Yuxuan Liu, Benny Lo, Guang-Zhong Yang
Two new datasets were proposed for this problem, named AWA2-LTS and ImageNet-LTS.
no code implementations • 11 Mar 2022 • Junhua Ma, Jiajun Li, Yuxuan Liu, Shangbo Zhou, Xue Li
Recent progress on parse tree encoder for sentence representation learning is notable.
no code implementations • 16 Feb 2022 • Zhenhua Xu, Yuxuan Liu, Lu Gan, Yuxiang Sun, Xinyu Wu, Ming Liu, Lujia Wang
To provide a solution to these problems, we propose a novel approach based on transformer and imitation learning in this paper.
no code implementations • 11 Nov 2021 • Zhenhua Xu, Yuxuan Liu, Lu Gan, Xiangcheng Hu, Yuxiang Sun, Ming Liu, Lujia Wang
To provide a solution to the aforementioned problems, in this letter, we propose a novel system termed csBoundary to automatically detect road boundaries at the city scale for HD map annotation.
no code implementations • 9 Nov 2021 • Fengda Zhang, Kun Kuang, Yuxuan Liu, Long Chen, Chao Wu, Fei Wu, Jiaxun Lu, Yunfeng Shao, Jun Xiao
We validate the advantages of the FMDA-M algorithm with various kinds of distribution shift settings in experiments, and the results show that FMDA-M algorithm outperforms the existing fair FL algorithms on unified group fairness.
1 code implementation • 18 Jul 2021 • Peide Cai, Hengli Wang, Huaiyang Huang, Yuxuan Liu, Ming Liu
In this work, we present a general deep imitative reinforcement learning approach (DIRL), which successfully achieves agile autonomous racing using visual inputs.
1 code implementation • 17 Mar 2021 • Yuxuan Liu, Lujia Wang, Ming Liu
Object detection in 3D with stereo cameras is an important problem in computer vision, and is particularly crucial in low-cost autonomous mobile robots without LiDARs.
3D Object Detection From Stereo Images Disparity Estimation +3
1 code implementation • 1 Feb 2021 • Yuxuan Liu, Yuan Yixuan, Ming Liu
We further verify the power of the proposed module with a neural network designed for monocular depth prediction.
Ranked #5 on Monocular 3D Object Detection on KITTI Cars Hard
no code implementations • 29 Nov 2020 • Lei Wang, Yuchun Huang, Pengjie Tao, Yaolin Hou, Yuxuan Liu
We study the problem of generating point clouds of 3D objects.
no code implementations • 21 Aug 2020 • Hengli Wang, Yuxuan Liu, Huaiyang Huang, Yuheng Pan, Wenbin Yu, Jialin Jiang, Dianbin Lyu, Mohammud J. Bocus, Ming Liu, Ioannis Pitas, Rui Fan
In this paper, we introduce a novel suspect-and-investigate framework, which can be easily embedded in a drone for automated parking violation detection (PVD).
no code implementations • 30 Mar 2020 • Yuxuan Liu, Jiangyong Duan, Juan Meng
In this paper, we propose a novel model for time series prediction in which difference-attention LSTM model and error-correction LSTM model are respectively employed and combined in a cascade way.
no code implementations • 10 Dec 2018 • Alex Bewley, Jessica Rigley, Yuxuan Liu, Jeffrey Hawke, Richard Shen, Vinh-Dieu Lam, Alex Kendall
Simulation can be a powerful tool for understanding machine learning systems and designing methods to solve real-world problems.
no code implementations • ICML 2018 • John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine
We show that we can learn continuous latent representations of trajectories, which are effective in solving temporally extended and multi-stage problems.
Hierarchical Reinforcement Learning reinforcement-learning +2
2 code implementations • NeurIPS 2018 • Abhishek Gupta, Russell Mendonca, Yuxuan Liu, Pieter Abbeel, Sergey Levine
Exploration is a fundamental challenge in reinforcement learning (RL).
1 code implementation • 11 Jul 2017 • YuXuan Liu, Abhishek Gupta, Pieter Abbeel, Sergey Levine
Imitation learning is an effective approach for autonomous systems to acquire control policies when an explicit reward function is unavailable, using supervision provided as demonstrations from an expert, typically a human operator.
no code implementations • 8 Mar 2017 • Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine
People can learn a wide range of tasks from their own experience, but can also learn from observing other creatures.
1 code implementation • 11 Sep 2014 • Lili Mou, Ge Li, Yuxuan Liu, Hao Peng, Zhi Jin, Yan Xu, Lu Zhang
In this pioneering paper, we propose the "coding criterion" to build program vector representations, which are the premise of deep learning for program analysis.