no code implementations • 18 Mar 2024 • Mohammad Jafari, Yimeng Zhang, Yihua Zhang, Sijia Liu
As machine learning tasks continue to evolve, the trend has been to gather larger datasets and train increasingly larger models.
1 code implementation • 19 Feb 2024 • Yihua Zhang, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Xiaoming Liu, Sijia Liu
The rapid advancement of diffusion models (DMs) has not only transformed various real-world industries but has also introduced negative societal concerns, including the generation of harmful content, copyright disputes, and the rise of stereotypes and biases.
1 code implementation • 18 Feb 2024 • Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen
In the evolving landscape of natural language processing (NLP), fine-tuning pre-trained Large Language Models (LLMs) with first-order (FO) optimizers like SGD and Adam has become standard.
1 code implementation • 15 Dec 2023 • Xiangde Luo, Jia Fu, Yunxin Zhong, Shuolin Liu, Bing Han, Mehdi Astaraki, Simone Bendazzoli, Iuliana Toma-Dasu, Yiwen Ye, Ziyang Chen, Yong Xia, Yanzhou Su, Jin Ye, Junjun He, Zhaohu Xing, Hongqiu Wang, Lei Zhu, Kaixiang Yang, Xin Fang, Zhiwei Wang, Chan Woong Lee, Sang Joon Park, Jaehee Chun, Constantin Ulrich, Klaus H. Maier-Hein, Nchongmaje Ndipenoch, Alina Miron, Yongmin Li, Yimeng Zhang, Yu Chen, Lu Bai, Jinlong Huang, Chengyang An, Lisheng Wang, Kaiwen Huang, Yunqi Gu, Tao Zhou, Mu Zhou, Shichuan Zhang, Wenjun Liao, Guotai Wang, Shaoting Zhang
The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis.
1 code implementation • 18 Oct 2023 • Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu
Our results demonstrate the effectiveness and efficiency merits of UnlearnDiffAtk over the state-of-the-art adversarial prompt generation method and reveal the lack of robustness of current safety-driven unlearning techniques when applied to DMs.
1 code implementation • 3 Oct 2023 • Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
Our extensive experiments show that DeepZero achieves state-of-the-art (SOTA) accuracy on ResNet-20 trained on CIFAR-10, approaching FO training performance for the first time.
no code implementations • 29 May 2023 • Qianjun Lyu, Wing Suen, Yimeng Zhang
We study an information design problem with continuous state and discrete signal space.
1 code implementation • CVPR 2023 • Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding
In this paper, we study the problem of temporal video grounding (TVG), which aims to predict the starting/ending time points of moments described by a text sentence within a long untrimmed video.
no code implementations • 6 Dec 2022 • Wenjun Xu, Yimeng Zhang, Fengyu Wang, Zhijin Qin, Chenyao Liu, Ping Zhang
Internet of Vehicles (IoV) is expected to become the central infrastructure to provide advanced services to connected vehicles and users for higher transportation efficiency and security.
no code implementations • 9 Nov 2022 • Jinghan Jia, Mingyi Hong, Yimeng Zhang, Mehmet Akçakaya, Sijia Liu
We find a new instability source of MRI image reconstruction, i. e., the lack of reconstruction robustness against spatial transformations of an input, e. g., rotation and cutout.
no code implementations • 16 Oct 2022 • Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan, Wuyang Chen, Zhangyang Wang, Shiyu Chang, Sijia Liu, Cong Hao
In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stream.
1 code implementation • ICLR 2022 • Yimeng Zhang, Yuguang Yao, Jinghan Jia, JinFeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
To tackle this problem, we next propose to prepend an autoencoder (AE) to a given (black-box) model so that DS can be trained using variance-reduced ZO optimization.
2 code implementations • ICLR 2022 • Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu
However, carefully crafted, tiny adversarial perturbations are difficult to recover by optimizing a unilateral RED objective.
no code implementations • 2 Oct 2021 • Yimeng Zhang, Harold Rockwell, Sicheng Dai, Ge Huang, Stephen Tsou, Yuanyuan Wei, Tai Sing Lee
Feedforward CNN models have proven themselves in recent years as state-of-the-art models for predicting single-neuron responses to natural images in early visual cortical neurons.
no code implementations • 11 Aug 2020 • Xiaofeng Liu, Yimeng Zhang, Xiongchang Liu, Song Bai, Site Li, Jane You
The ground metric of Wasserstein distance can be pre-defined following the experience on a specific task.
no code implementations • 22 Dec 2019 • Siming Yan, Xuyang Fang, Bowen Xiao, Harold Rockwell, Yimeng Zhang, Tai Sing Lee
The abundant recurrent horizontal and feedback connections in the primate visual cortex are thought to play an important role in bringing global and semantic contextual information to early visual areas during perceptual inference, helping to resolve local ambiguity and fill in missing details.
no code implementations • 19 Nov 2019 • Ziniu Wu, Harold Rockwell, Yimeng Zhang, Shiming Tang, Tai Sing Lee
System identification techniques -- projection pursuit regression models (PPRs) and convolutional neural networks (CNNs) -- provide state-of-the-art performance in predicting visual cortical neurons' responses to arbitrary input stimuli.
no code implementations • ICLR 2019 • Siming Yan*, Bowen Xiao*, Yimeng Zhang, Tai Sing Lee
In this work, we designed a Contextual Recurrent Convolutional Network with this feature embedded in a standard CNN structure.
no code implementations • 22 May 2017 • Hao Wang, Xingyu Lin, Yimeng Zhang, Tai Sing Lee
Trained on imagined occluded scenarios under the object persistence constraint, our network discovered more subtle and localized image features that were neglected by the original network for object classification, obtaining better separability of different object classes in the feature space.
no code implementations • 31 Mar 2017 • Xingyu Lin, Hao Wang, Zhihao LI, Yimeng Zhang, Alan Yuille, Tai Sing Lee
We develop a model of perceptual similarity judgment based on re-training a deep convolution neural network (DCNN) that learns to associate different views of each 3D object to capture the notion of object persistence and continuity in our visual experience.