1 code implementation • 18 Jan 2024 • Qingyun Wang, Zixuan Zhang, Hongxiang Li, Xuan Liu, Jiawei Han, Huimin Zhao, Heng Ji
Fine-grained few-shot entity extraction in the chemical domain faces two unique challenges.
no code implementations • 9 Jan 2024 • Jiaqi Wang, Zihao Wu, Yiwei Li, Hanqi Jiang, Peng Shu, Enze Shi, Huawen Hu, Chong Ma, Yiheng Liu, Xuhui Wang, Yincheng Yao, Xuan Liu, Huaqin Zhao, Zhengliang Liu, Haixing Dai, Lin Zhao, Bao Ge, Xiang Li, Tianming Liu, Shu Zhang
Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions.
1 code implementation • 25 Dec 2023 • Yongkang Wang, Xuan Liu, Feng Huang, Zhankun Xiong, Wen Zhang
Therapeutic peptides represent a unique class of pharmaceutical agents crucial for the treatment of human diseases.
1 code implementation • 16 Nov 2023 • Siru Ouyang, Zhuosheng Zhang, Bing Yan, Xuan Liu, Yejin Choi, Jiawei Han, Lianhui Qin
Large Language Models (LLMs) excel in diverse areas, yet struggle with complex scientific reasoning, especially in the field of chemistry.
1 code implementation • 1 Nov 2023 • Xuan Liu, Jinglong Chen, Jingsong Xie, Yuanhong Chang
VGCDM also incorporates control pulse voltage by cross-attention mechanism to ensure the alignment of vibration with voltage signals, enhancing the Conditional Diffusion Model's progressive controlablity.
1 code implementation • 21 Sep 2023 • Jiaxin Zhang, Shiyuan Chen, Haoran Yin, Ruohong Mei, Xuan Liu, Cong Yang, Qian Zhang, Wei Sui
The recent development of online static map element (a. k. a.
1 code implementation • 31 Aug 2023 • Xuan Liu, Yaoqin Xie, Songhui Diao, Shan Tan, Xiaokun Liang
In this paper, we propose an unsupervised MAR method based on the diffusion model, a generative model with a high capacity to represent data distributions.
no code implementations • 28 Jul 2023 • Risheng Liu, Jiaxin Gao, Xuan Liu, Xin Fan
The complexity of learning problems, such as Generative Adversarial Network (GAN) and its variants, multi-task and meta-learning, hyper-parameter learning, and a variety of real-world vision applications, demands a deeper understanding of their underlying coupling mechanisms.
no code implementations • 31 May 2023 • Chulong Zhang, Lin Liu, Jingjing Dai, Xuan Liu, Wenfeng He, Yinping Chan, Yaoqin Xie, Feng Chi, Xiaokun Liang
Computed tomography (CT) scans offer a detailed, three-dimensional representation of patients' internal organs.
1 code implementation • 25 May 2023 • Xuan Liu, Yaoqin Xie, Jun Cheng, Songhui Diao, Shan Tan, Xiaokun Liang
The results demonstrate that our method outperforms the state-of-the-art unsupervised method and surpasses several supervised deep learning-based methods.
no code implementations • 11 Feb 2023 • Risheng Liu, Xuan Liu, Shangzhi Zeng, Jin Zhang, Yixuan Zhang
In recent years, by utilizing optimization techniques to formulate the propagation of deep model, a variety of so-called Optimization-Derived Learning (ODL) approaches have been proposed to address diverse learning and vision tasks.
no code implementations • 16 Jun 2022 • Risheng Liu, Xuan Liu, Shangzhi Zeng, Jin Zhang, Yixuan Zhang
Recently, Optimization-Derived Learning (ODL) has attracted attention from learning and vision areas, which designs learning models from the perspective of optimization.
no code implementations • 20 May 2022 • Risheng Liu, Xuan Liu, Wei Yao, Shangzhi Zeng, Jin Zhang
Gradient methods have become mainstream techniques for Bi-Level Optimization (BLO) in learning and vision fields.
no code implementations • 20 May 2022 • Risheng Liu, Jiaxin Gao, Xuan Liu, Xin Fan
In past years, the minimax type single-level optimization formulation and its variations have been widely utilized to address Generative Adversarial Networks (GANs).
1 code implementation • 11 Oct 2021 • Risheng Liu, Xuan Liu, Shangzhi Zeng, Jin Zhang, Yixuan Zhang
We also extend BVFSM to address BLO with additional functional constraints.
no code implementations • 4 Oct 2021 • Brian Quanz, Ajay Deshpande, Dahai Xing, Xuan Liu
Essentially, those assignments that can be predicted with high confidence can be used to shortcut, or bypass, the expensive deciding process, or else a set of most likely assignments can be used for shortlisting -- sending a much smaller set of candidates for consideration by the fulfillment deciding system.
no code implementations • 15 Jun 2021 • Risheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
Bi-level optimization model is able to capture a wide range of complex learning tasks with practical interest.
no code implementations • 3 Jun 2021 • Vishrawas Gopalakrishnan, Sayali Navalekar, Pan Ding, Ryan Hooley, Jacob Miller, Raman Srinivasan, Ajay Deshpande, Xuan Liu, Simone Bianco, James H. Kaufman
Pandemic control measures like lock-down, restrictions on restaurants and gatherings, social-distancing have shown to be effective in curtailing the spread of COVID-19.
1 code implementation • ACL 2021 • ZiYun Wang, Xuan Liu, Peiji Yang, Shixing Liu, Zhisheng Wang
Cross-lingual text classification aims at training a classifier on the source language and transferring the knowledge to target languages, which is very useful for low-resource languages.
no code implementations • 1 Feb 2021 • S. H. Alsamhi, B. Lee, M. Guizani, N. Kumar, Y. Qiao, Xuan Liu
Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak.
Distributed, Parallel, and Cluster Computing Systems and Control Systems and Control
1 code implementation • ICCV 2021 • Haosen Liu, Xuan Liu, Jiangbo Lu, Shan Tan
It can simultaneously achieve the noise level estimation and the image prior learning directly from only a single noisy image.
no code implementations • 20 Aug 2020 • Jun Jiang, Xuan Liu, Scott Wallace, Eduardo Cotilla-Sanchez, Robert Bass, Xinghui Zhao
Phasor measurement units (PMUs) provide high-fidelity data that improve situation awareness of electric power grid operations.
no code implementations • 13 Jan 2020 • Xuan Liu, Renato Gasoto, Cagdas Onal, Jie Fu
Inspired by biological snakes, our control architecture is composed of two key modules: A deep reinforcement learning (RL) module for achieving adaptive goal-tracking behaviors with changing goals, and a central pattern generator (CPG) system with Matsuoka oscillators for generating stable and diverse locomotion patterns.
no code implementations • 28 Dec 2018 • Xuan Liu, Xiaoguang Wang, Stan Matwin
To tackle this problem, we apply the Knowledge Distillation technique to distill Deep Neural Networks into decision trees in order to attain good performance and interpretability simultaneously.
no code implementations • 5 Oct 2018 • Xuan Liu, Jie Fu
Thus, a synthesis algorithm is developed to compute optimal policies efficiently by planning with primitive actions, policies for sub-tasks, and the compositions of sub-policies, for maximizing the probability of satisfying temporal logic specifications.
no code implementations • NAACL 2018 • Xuan Liu, Di Cao, Kai Yu
Although excellent performance is obtained for large vocabulary tasks, tremendous memory consumption prohibits the use of LSTM LM in low-resource devices.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 2 Feb 2018 • Xuan Liu, Xiaoguang Wang, Stan Matwin
We attempt to address this challenge by proposing a technique called CNN-INTE to interpret deep Convolutional Neural Networks (CNN) via meta-learning.
3 code implementations • WS 2018 • Wei He, Kai Liu, Jing Liu, Yajuan Lyu, Shiqi Zhao, Xinyan Xiao, Yu-An Liu, Yizhong Wang, Hua Wu, Qiaoqiao She, Xuan Liu, Tian Wu, Haifeng Wang
Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.
no code implementations • 16 Oct 2015 • Chenhao Zhu, Kan Ren, Xuan Liu, Haofen Wang, Yiding Tian, Yong Yu
We present a question answering system over DBpedia, filling the gap between user information needs expressed in natural language and a structured query interface expressed in SPARQL over the underlying knowledge base (KB).