Search Results for author: Xuan Liu

Found 31 papers, 12 papers with code

Advancing Generalized Transfer Attack with Initialization Derived Bilevel Optimization and Dynamic Sequence Truncation

1 code implementation4 Jun 2024 Yaohua Liu, Jiaxin Gao, Xuan Liu, Xianghao Jiao, Xin Fan, Risheng Liu

Transfer attacks generate significant interest for real-world black-box applications by crafting transferable adversarial examples through surrogate models.

Bilevel Optimization

Large Language Models for Robotics: Opportunities, Challenges, and Perspectives

no code implementations9 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.

Robot Task Planning

A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation

1 code implementation25 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.

Contrastive Learning

Structured Chemistry Reasoning with Large Language Models

1 code implementation16 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.

General Knowledge

Generating HSR Bogie Vibration Signals via Pulse Voltage-Guided Conditional Diffusion Model

1 code implementation1 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.

Denoising

Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains

1 code implementation31 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.

Computed Tomography (CT) Metal Artifact Reduction

Learning with Constraint Learning: New Perspective, Solution Strategy and Various Applications

no code implementations28 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.

Generative Adversarial Network Meta-Learning

Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising

1 code implementation25 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.

Computed Tomography (CT) Image Denoising

Hierarchical Optimization-Derived Learning

no code implementations11 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.

Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training

no code implementations16 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.

Image Deconvolution

Towards Extremely Fast Bilevel Optimization with Self-governed Convergence Guarantees

no code implementations20 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.

Bilevel Optimization

Revisiting GANs by Best-Response Constraint: Perspective, Methodology, and Application

no code implementations20 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).

Value-Function-based Sequential Minimization for Bi-level Optimization

1 code implementation11 Oct 2021 Risheng Liu, Xuan Liu, Shangzhi Zeng, Jin Zhang, Yixuan Zhang

We also extend BVFSM to address BLO with additional functional constraints.

Learning to shortcut and shortlist order fulfillment deciding

no code implementations4 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.

A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization

no code implementations15 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.

Adaptive Epidemic Forecasting and Community Risk Evaluation of COVID-19

no code implementations3 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.

Benchmarking Decision Making

Cross-lingual Text Classification with Heterogeneous Graph Neural Network

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.

Graph Neural Network Semantic Similarity +3

Blockchain for Decentralized Multi-Drone to Combat COVID-19

no code implementations1 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

Self-Supervised Image Prior Learning With GMM From a Single Noisy Image

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.

Image Denoising Noise Estimation +1

Learning to Locomote with Deep Neural-Network and CPG-based Control in a Soft Snake Robot

no code implementations13 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.

Reinforcement Learning (RL)

Improving the Interpretability of Deep Neural Networks with Knowledge Distillation

no code implementations28 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.

Ethics Knowledge Distillation +3

Compositional planning in Markov decision processes: Temporal abstraction meets generalized logic composition

no code implementations5 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.

Binarized LSTM Language Model

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

Interpretable Deep Convolutional Neural Networks via Meta-learning

no code implementations2 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.

Clustering Fairness +1

DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

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.

Machine Reading Comprehension

A Graph Traversal Based Approach to Answer Non-Aggregation Questions Over DBpedia

no code implementations16 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).

Question Answering

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