no code implementations • 5 Jun 2024 • Sheng Zhou, Yukuan Jia, Ruiqing Mao, Zhaojun Nan, Yuxuan Sun, Zhisheng Niu
In this article, a task-oriented wireless communication framework is proposed to jointly optimize the communication scheme and the CP procedure.
no code implementations • 29 Jan 2024 • Yuxuan Sun, Hao Wu, Chenglu Zhu, Sunyi Zheng, Qizi Chen, Kai Zhang, Yunlong Zhang, Dan Wan, Xiaoxiao Lan, Mengyue Zheng, Jingxiong Li, Xinheng Lyu, Tao Lin, Lin Yang
To address this, we introduce PathMMU, the largest and highest-quality expert-validated pathology benchmark for Large Multimodal Models (LMMs).
no code implementations • 18 Jan 2024 • Tan Chen, Jintao Yan, Yuxuan Sun, Sheng Zhou, Deniz Gündüz, Zhisheng Niu
Hierarchical federated learning (HFL) enables distributed training of models across multiple devices with the help of several edge servers and a cloud edge server in a privacy-preserving manner.
no code implementations • 5 Jan 2024 • Sunyi Zheng, Xiaonan Cui, Yuxuan Sun, Jingxiong Li, Honglin Li, Yunlong Zhang, Pingyi Chen, Xueping Jing, Zhaoxiang Ye, Lin Yang
Additionally, we assess the robustness of PathCLIP in the task of image-image retrieval, revealing that PathCLIP performs less effectively than PLIP on Osteosarcoma but performs better on WSSS4LUAD under diverse corruptions.
no code implementations • 5 Dec 2023 • Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Janice Ahn, Hanzi Xu, Yu Su, Wenpeng Yin
In the realm of large language models (LLMs), enhancing instruction-following capability often involves curating expansive training data.
1 code implementation • 27 Nov 2023 • Zhongyi Shui, Yunlong Zhang, Kai Yao, Chenglu Zhu, Sunyi Zheng, Jingxiong Li, Honglin Li, Yuxuan Sun, Ruizhe Guo, Lin Yang
In this paper, we present a novel prompt-driven framework that consists of a nucleus prompter and SAM for automatic nucleus instance segmentation.
3 code implementations • 27 Nov 2023 • Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, Cong Wei, Botao Yu, Ruibin Yuan, Renliang Sun, Ming Yin, Boyuan Zheng, Zhenzhu Yang, Yibo Liu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen
We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning.
1 code implementation • 14 Nov 2023 • Yunlong Zhang, Yuxuan Sun, Sunyi Zheng, Zhongyi Shui, Chenglu Zhu, Lin Yang
Although deep learning-based segmentation models have achieved impressive performance on public benchmarks, generalizing well to unseen environments remains a major challenge.
1 code implementation • 13 Nov 2023 • Yunlong Zhang, Honglin Li, Yuxuan Sun, Sunyi Zheng, Chenglu Zhu, Lin Yang
In the application of Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) classification, attention mechanisms often focus on a subset of discriminative instances, which are closely linked to overfitting.
1 code implementation • 4 Oct 2023 • Yuxuan Sun, Kai Zhang, Yu Su
In addition, the effectiveness of our framework can successfully transfer to the few-shot setting, enhancing LMMs on a scale of 10B parameters to be competitive or outperform much larger language models such as ChatGPT and GPT-4.
1 code implementation • 14 Sep 2023 • Jack Lanchantin, Sainbayar Sukhbaatar, Gabriel Synnaeve, Yuxuan Sun, Kavya Srinet, Arthur Szlam
In this work, to further pursue these advances, we introduce a new data generator for machine reasoning that integrates with an embodied agent.
no code implementations • 25 Jun 2023 • Jingxiong Li, Sunyi Zheng, Zhongyi Shui, Shichuan Zhang, Linyi Yang, Yuxuan Sun, Yunlong Zhang, Honglin Li, Yuanxin Ye, Peter M. A. van Ooijen, Kang Li, Lin Yang
This yields a non-trivial reconstruction task, allowing the model to effectively preserve chromosome banding patterns and structure details in the reconstructed results.
no code implementations • 19 Jun 2023 • Tan Chen, Jintao Yan, Yuxuan Sun, Sheng Zhou, Deniz Gunduz, Zhisheng Niu
Federated learning enables distributed training of machine learning (ML) models across multiple devices in a privacy-preserving manner.
1 code implementation • 24 May 2023 • Yuxuan Sun, Chenglu Zhu, Sunyi Zheng, Kai Zhang, Lin Sun, Zhongyi Shui, Yunlong Zhang, Honglin Li, Lin Yang
Secondly, by leveraging the collected data, we construct PathCLIP, a pathology-dedicated CLIP, to enhance PathAsst's capabilities in interpreting pathology images.
no code implementations • 22 May 2023 • Lei Guo, Wei Chen, Yuxuan Sun, Bo Ai
Additionally, structured pruning is incorporated to reduce the dimension of the transmitted features.
1 code implementation • 18 May 2023 • Shrestha Mohanty, Negar Arabzadeh, Julia Kiseleva, Artem Zholus, Milagro Teruel, Ahmed Awadallah, Yuxuan Sun, Kavya Srinet, Arthur Szlam
Human intelligence's adaptability is remarkable, allowing us to adjust to new tasks and multi-modal environments swiftly.
1 code implementation • CVPR 2023 • Honglin Li, Chenglu Zhu, Yunlong Zhang, Yuxuan Sun, Zhongyi Shui, Wenwei Kuang, Sunyi Zheng, Lin Yang
Our framework is evaluated on five pathology WSI datasets on various WSI heads.
no code implementations • 25 Feb 2023 • Yukuan Jia, Ruiqing Mao, Yuxuan Sun, Sheng Zhou, Zhisheng Niu
Specifically, we design a mobility-aware sensor scheduling (MASS) algorithm based on the restless multi-armed bandit (RMAB) theory to maximize the expected average perception gain.
no code implementations • 7 Dec 2022 • Bowen Xie, Yuxuan Sun, Sheng Zhou, Zhisheng Niu, Yang Xu, Jingran Chen, Deniz Gündüz
Federated learning (FL) is a promising approach to enable the future Internet of vehicles consisting of intelligent connected vehicles (ICVs) with powerful sensing, computing and communication capabilities.
2 code implementations • 12 Nov 2022 • Shrestha Mohanty, Negar Arabzadeh, Milagro Teruel, Yuxuan Sun, Artem Zholus, Alexey Skrynnik, Mikhail Burtsev, Kavya Srinet, Aleksandr Panov, Arthur Szlam, Marc-Alexandre Côté, Julia Kiseleva
Human intelligence can remarkably adapt quickly to new tasks and environments.
no code implementations • 27 Oct 2022 • Yuxuan Sun, Bowen Xie, Sheng Zhou, Zhisheng Niu
Accordingly, base stations (BSs) and edge servers (ESs) need to be densely deployed, leading to huge deployment and operation costs, in particular the energy costs.
1 code implementation • 17 Jul 2022 • Lei Zhang, Yuxuan Sun, Wei Wei
Instead of directly exploiting the pseudo labels produced by the teacher detector, we take the first attempt at reducing their deviation from ground truth using dual polishing learning, where two differently structured polishing networks are elaborately developed and trained using synthesized paired pseudo labels and the corresponding ground truth for categories and bounding boxes on the given annotated objects, respectively.
Ranked #10 on Semi-Supervised Object Detection on COCO 5% labeled data
1 code implementation • 15 Jul 2022 • Ruiqing Mao, Jingyu Guo, Yukuan Jia, Yuxuan Sun, Sheng Zhou, Zhisheng Niu
In this work, we release DOLPHINS: Dataset for cOllaborative Perception enabled Harmonious and INterconnected Self-driving, as a new simulated large-scale various-scenario multi-view multi-modality autonomous driving dataset, which provides a ground-breaking benchmark platform for interconnected autonomous driving.
1 code implementation • 30 Jun 2022 • Yunlong Zhang, Yuxuan Sun, Honglin Li, Sunyi Zheng, Chenglu Zhu, Lin Yang
Evaluated on two resulting benchmark datasets, we find that (1) a variety of deep neural network models suffer from a significant accuracy decrease (double the error on clean images) and the unreliable confidence estimation on corrupted images; (2) A low correlation between the validation and test errors while replacing the validation set with our benchmark can increase the correlation.
1 code implementation • 27 May 2022 • Julia Kiseleva, Alexey Skrynnik, Artem Zholus, Shrestha Mohanty, Negar Arabzadeh, Marc-Alexandre Côté, Mohammad Aliannejadi, Milagro Teruel, Ziming Li, Mikhail Burtsev, Maartje ter Hoeve, Zoya Volovikova, Aleksandr Panov, Yuxuan Sun, Kavya Srinet, Arthur Szlam, Ahmed Awadallah
Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions.
no code implementations • 5 May 2022 • Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Marc-Alexandre Côté, Katja Hofmann, Ahmed Awadallah, Linar Abdrazakov, Igor Churin, Putra Manggala, Kata Naszadi, Michiel van der Meer, Taewoon Kim
The primary goal of the competition is to approach the problem of how to build interactive agents that learn to solve a task while provided with grounded natural language instructions in a collaborative environment.
no code implementations • 19 Apr 2022 • Yuxuan Sun, Ethan Carlson, Rebecca Qian, Kavya Srinet, Arthur Szlam
In this work we give a case study of an embodied machine-learning (ML) powered agent that improves itself via interactions with crowd-workers.
no code implementations • 17 Feb 2022 • Yuxuan Sun, Sheng Zhou, Zhisheng Niu, Deniz Gündüz
In this work, we propose time-correlated sparsification with hybrid aggregation (TCS-H) for communication-efficient FEEL, which exploits jointly the power of model compression and over-the-air computation.
no code implementations • 12 Feb 2022 • Yukuan Jia, Ruiqing Mao, Yuxuan Sun, Sheng Zhou, Zhisheng Niu
Cooperative perception of connected vehicles comes to the rescue when the field of view restricts stand-alone intelligence.
no code implementations • 13 Oct 2021 • Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Katja Hofmann, Michel Galley, Ahmed Awadallah
Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions.
no code implementations • 23 Sep 2021 • Yuxuan Sun, Fan Zhang, Junlin Zhao, Sheng Zhou, Zhisheng Niu, Deniz Gündüz
In this work, we consider a multi-master heterogeneous-worker distributed computing scenario, where multiple matrix multiplication tasks are encoded and allocated to workers for parallel computation.
no code implementations • 2 Jul 2021 • Jerrick Liu, Nathan Inkawhich, Oliver Nina, Radu Timofte, Sahil Jain, Bob Lee, Yuru Duan, Wei Wei, Lei Zhang, Songzheng Xu, Yuxuan Sun, Jiaqi Tang, Mengru Ma, Gongzhe Li, Xueli Geng, Huanqia Cai, Chengxue Cai, Sol Cummings, Casian Miron, Alexandru Pasarica, Cheng-Yen Yang, Hung-Min Hsu, Jiarui Cai, Jie Mei, Chia-Ying Yeh, Jenq-Neng Hwang, Michael Xin, Zhongkai Shangguan, Zihe Zheng, Xu Yifei, Lehan Yang, Kele Xu, Min Feng
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR.
no code implementations • 31 May 2021 • Yuxuan Sun, Sheng Zhou, Zhisheng Niu, Deniz Gündüz
In this work, we consider an over-the-air FEEL system with analog gradient aggregation, and propose an energy-aware dynamic device scheduling algorithm to optimize the training performance under energy constraints of devices, where both communication energy for gradient aggregation and computation energy for local training are included.
1 code implementation • 25 Jan 2021 • Anurag Pratik, Soumith Chintala, Kavya Srinet, Dhiraj Gandhi, Rebecca Qian, Yuxuan Sun, Ryan Drew, Sara Elkafrawy, Anoushka Tiwari, Tucker Hart, Mary Williamson, Abhinav Gupta, Arthur Szlam
In recent years, there have been significant advances in building end-to-end Machine Learning (ML) systems that learn at scale.
no code implementations • COLING 2020 • Lin Sun, Jiquan Wang, Yindu Su, Fangsheng Weng, Yuxuan Sun, Zengwei Zheng, Yuanyi Chen
In the multimodal NER task, the experimental results show the significance of text-related visual features for the visual-linguistic model and our approach achieves SOTA performance on the MNER datasets.
1 code implementation • CVPR 2019 • Yuxuan Sun, Chong Sun, Dong Wang, You He, Huchuan Lu
The ROI (region-of-interest) based pooling method performs pooling operations on the cropped ROI regions for various samples and has shown great success in the object detection methods.
no code implementations • 1 Nov 2019 • Yuxuan Sun, Sheng Zhou, Deniz Gündüz
In this work, we consider analog aggregation to scale down the communication cost with respect to the number of workers, and introduce data redundancy to the system to deal with non-i. i. d.