Search Results for author: Yuxuan Sun

Found 41 papers, 18 papers with code

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration

1 code implementation28 Jun 2024 Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Zhongyi Shui, Kai Zhang, Jingxiong Li, Xingheng Lyu, Tao Lin, Lin Yang

Vision Language Models (VLMs) like CLIP have attracted substantial attention in pathology, serving as backbones for applications such as zero-shot image classification and Whole Slide Image (WSI) analysis.

Image Classification Zero-Shot Image Classification

Dynamic Scheduling for Vehicle-to-Vehicle Communications Enhanced Federated Learning

no code implementations25 Jun 2024 Jintao Yan, Tan Chen, Yuxuan Sun, Zhaojun Nan, Sheng Zhou, Zhisheng Niu

In this paper, we formulate a stochastic optimization problem to optimize the VFL training performance, considering the energy constraints and mobility of vehicles, and propose a V2V-enhanced dynamic scheduling (VEDS) algorithm to solve it.

Federated Learning Image Classification +3

Task-Oriented Wireless Communications for Collaborative Perception in Intelligent Unmanned Systems

no code implementations5 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.

Autonomous Driving Scheduling

VideoQA-SC: Adaptive Semantic Communication for Video Question Answering

no code implementations17 May 2024 Jiangyuan Guo, Wei Chen, Yuxuan Sun, Jialong Xu, Bo Ai

The difficulty in such system design lies in the extraction of task-related compact semantic representations and their accurate delivery over noisy channels.

Question Answering Semantic Communication +2

PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology

no code implementations29 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).

Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks

no code implementations18 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.

Federated Learning Privacy Preserving

Benchmarking PathCLIP for Pathology Image Analysis

no code implementations5 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.

Benchmarking Decision Making +4

MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following

no code implementations5 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.

Instruction Following

Unleashing the Power of Prompt-driven Nucleus Instance Segmentation

1 code implementation27 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.

Image Segmentation Instance Segmentation +3

Test-Time Training for Semantic Segmentation with Output Contrastive Loss

1 code implementation14 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.

Domain Adaptation Image Classification +1

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification

1 code implementation13 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.

Image Classification Multiple Instance Learning

Multimodal Question Answering for Unified Information Extraction

1 code implementation4 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.

Diversity Question Answering

A Data Source for Reasoning Embodied Agents

1 code implementation14 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.

Masked conditional variational autoencoders for chromosome straightening

no code implementations25 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.

Data-Heterogeneous Hierarchical Federated Learning with Mobility

no code implementations19 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.

Federated Learning Privacy Preserving

PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

1 code implementation24 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.

Instruction Following Language Modelling +1

MASS: Mobility-Aware Sensor Scheduling of Cooperative Perception for Connected Automated Driving

no code implementations25 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.


MOB-FL: Mobility-Aware Federated Learning for Intelligent Connected Vehicles

no code implementations7 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.

Federated Learning Trajectory Prediction

MEET: Mobility-Enhanced Edge inTelligence for Smart and Green 6G Networks

no code implementations27 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.

Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised Object Detection

1 code implementation17 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.

object-detection Object Detection +2

DOLPHINS: Dataset for Collaborative Perception enabled Harmonious and Interconnected Self-driving

1 code implementation15 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.

Autonomous Driving Object Detection

Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology

1 code implementation30 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.


Many Episode Learning in a Modular Embodied Agent via End-to-End Interaction

no code implementations19 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.

Time-Correlated Sparsification for Efficient Over-the-Air Model Aggregation in Wireless Federated Learning

no code implementations17 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.

Federated Learning Model Compression +1

Online V2X Scheduling for Raw-Level Cooperative Perception

no code implementations12 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.


Coded Computation across Shared Heterogeneous Workers with Communication Delay

no code implementations23 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.

Distributed Computing

Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints

no code implementations31 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.


droidlet: modular, heterogenous, multi-modal agents

1 code implementation25 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.

RIVA: A Pre-trained Tweet Multimodal Model Based on Text-image Relation for Multimodal NER

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.

named-entity-recognition Named Entity Recognition +3

ROI Pooled Correlation Filters for Visual Tracking

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.

object-detection Object Detection +1

Energy-Aware Analog Aggregation for Federated Learning with Redundant Data

no code implementations1 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.

Federated Learning Scheduling

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