Search Results for author: Yuxin Liu

Found 11 papers, 2 papers with code

Generative AI to Generate Test Data Generators

no code implementations31 Jan 2024 Benoit Baudry, Khashayar Etemadi, Sen Fang, Yogya Gamage, Yi Liu, Yuxin Liu, Martin Monperrus, Javier Ron, André Silva, Deepika Tiwari

The results show that LLMs can successfully generate realistic test data generators in a wide range of domains at all three levels of integrability.

Step-size Optimization for Continual Learning

no code implementations30 Jan 2024 Thomas Degris, Khurram Javed, Arsalan SharifNassab, Yuxin Liu, Richard Sutton

We conclude by suggesting that combining both approaches could be a promising future direction to improve the performance of neural networks in continual learning.

Continual Learning

Text-Guided Texturing by Synchronized Multi-View Diffusion

no code implementations21 Nov 2023 Yuxin Liu, Minshan Xie, Hanyuan Liu, Tien-Tsin Wong

In this paper, we propose a synchronized multi-view diffusion approach that allows the diffusion processes from different views to reach a consensus of the generated content early in the process, and hence ensures the texture consistency.

Denoising

P2CADNet: An End-to-End Reconstruction Network for Parametric 3D CAD Model from Point Clouds

no code implementations4 Oct 2023 Zhihao Zong, Fazhi He, Rubin Fan, Yuxin Liu

Computer Aided Design (CAD), especially the feature-based parametric CAD, plays an important role in modern industry and society.

Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance

no code implementations1 Jun 2023 Jinbo Xing, Menghan Xia, Yuxin Liu, Yuechen Zhang, Yong Zhang, Yingqing He, Hanyuan Liu, Haoxin Chen, Xiaodong Cun, Xintao Wang, Ying Shan, Tien-Tsin Wong

Our method, dubbed Make-Your-Video, involves joint-conditional video generation using a Latent Diffusion Model that is pre-trained for still image synthesis and then promoted for video generation with the introduction of temporal modules.

Image Generation Video Generation

Teacher Forcing Recovers Reward Functions for Text Generation

1 code implementation17 Oct 2022 Yongchang Hao, Yuxin Liu, Lili Mou

We additionally propose a simple modification to stabilize the RL training on non-parallel datasets with our induced reward function.

regression reinforcement-learning +2

Large Scale Visual Food Recognition

no code implementations30 Mar 2021 Weiqing Min, Zhiling Wang, Yuxin Liu, Mengjiang Luo, Liping Kang, Xiaoming Wei, Xiaolin Wei, Shuqiang Jiang

Food2K can be further explored to benefit more food-relevant tasks including emerging and more complex ones (e. g., nutritional understanding of food), and the trained models on Food2K can be expected as backbones to improve the performance of more food-relevant tasks.

Fine-Grained Visual Recognition Food Recognition +3

Cue-word Driven Neural Response Generation with a Shrinking Vocabulary

1 code implementation10 Oct 2020 Qiansheng Wang, Yuxin Liu, Chengguo Lv, Zhen Wang, Guohong Fu

Open-domain response generation is the task of generating sensible and informative re-sponses to the source sentence.

Response Generation Sentence

Data-driven surrogate modelling and benchmarking for process equipment

no code implementations13 Mar 2020 Gabriel F. N. Gonçalves, Assen Batchvarov, Yuyi Liu, Yuxin Liu, Lachlan Mason, Indranil Pan, Omar K. Matar

In chemical process engineering, surrogate models of complex systems are often necessary for tasks of domain exploration, sensitivity analysis of the design parameters, and optimization.

Active Learning Benchmarking +2

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