Search Results for author: Mingyuan Ma

Found 15 papers, 8 papers with code

CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models

1 code implementation25 May 2025 Qinsi Wang, Hancheng Ye, Ming-Yu Chung, Yudong Liu, Yueqian Lin, Martin Kuo, Mingyuan Ma, Jianyi Zhang, Yiran Chen

Building on this insight, we propose CoreMatching, a co-adaptive sparse inference framework, which leverages the synergy between token and neuron sparsity to enhance inference efficiency.

Prism: Unleashing GPU Sharing for Cost-Efficient Multi-LLM Serving

no code implementations6 May 2025 Shan Yu, Jiarong Xing, Yifan Qiao, Mingyuan Ma, Yangmin Li, Yang Wang, Shuo Yang, Zhiqiang Xie, Shiyi Cao, Ke Bao, Ion Stoica, Harry Xu, Ying Sheng

At its core, Prism tackles a key limitation of existing systems$\unicode{x2014}$the lack of $\textit{cross-model memory coordination}$, which is essential for flexibly sharing GPU memory across models under dynamic workloads.

Scheduling

Multi-Cali Anything: Dense Feature Multi-Frame Structure-from-Motion for Large-Scale Camera Array Calibration

1 code implementation2 Mar 2025 Jinjiang You, Hewei Wang, Yijie Li, Mingxiao Huo, Long Van Tran Ha, Mingyuan Ma, Jinfeng Xu, Puzhen Wu, Shubham Garg, Wei Pu

Our approach enhances traditional Structure-from-Motion (SfM) pipelines by introducing an extrinsics regularization term to progressively align estimated extrinsics with ground-truth values, a dense feature reprojection term to reduce keypoint errors by minimizing reprojection loss in the feature space, and an intrinsics variance term for joint optimization across multiple frames.

3D Reconstruction

A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models

no code implementations8 Oct 2024 Cong Guo, Feng Cheng, Zhixu Du, James Kiessling, Jonathan Ku, Shiyu Li, Ziru Li, Mingyuan Ma, Tergel Molom-Ochir, Benjamin Morris, Haoxuan Shan, Jingwei Sun, Yitu Wang, Chiyue Wei, Xueying Wu, Yuhao Wu, Hao Frank Yang, Jingyang Zhang, Junyao Zhang, Qilin Zheng, Guanglei Zhou, Hai, Li, Yiran Chen

The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language processing and moving towards multi-modal functionality.

Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers

3 code implementations12 Aug 2024 Zhenting Qi, Mingyuan Ma, Jiahang Xu, Li Lyna Zhang, Fan Yang, Mao Yang

This paper introduces rStar, a self-play mutual reasoning approach that significantly improves reasoning capabilities of small language models (SLMs) without fine-tuning or superior models.

GSM8K Math +1

Octopus: On-device language model for function calling of software APIs

no code implementations2 Apr 2024 Wei Chen, Zhiyuan Li, Mingyuan Ma

In the rapidly evolving domain of artificial intelligence, Large Language Models (LLMs) play a crucial role due to their advanced text processing and generation abilities.

Language Modeling Language Modelling

Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching

no code implementations6 Apr 2023 Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West

Cross-device user matching is a critical problem in numerous domains, including advertising, recommender systems, and cybersecurity.

Graph Neural Network

Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models

2 code implementations ICCV 2023 Zangwei Zheng, Mingyuan Ma, Kai Wang, Ziheng Qin, Xiangyu Yue, Yang You

To address this challenge, we propose a novel method ZSCL to prevent zero-shot transfer degradation in the continual learning of vision-language models in both feature and parameter space.

class-incremental learning Class Incremental Learning +1

PIDS: Joint Point Interaction-Dimension Search for 3D Point Cloud

1 code implementation28 Nov 2022 Tunhou Zhang, Mingyuan Ma, Feng Yan, Hai Li, Yiran Chen

In this work, we establish PIDS, a novel paradigm to jointly explore point interactions and point dimensions to serve semantic segmentation on point cloud data.

Neural Architecture Search Robust 3D Semantic Segmentation +1

FADE: Enabling Federated Adversarial Training on Heterogeneous Resource-Constrained Edge Devices

no code implementations8 Sep 2022 Minxue Tang, Jianyi Zhang, Mingyuan Ma, Louis DiValentin, Aolin Ding, Amin Hassanzadeh, Hai Li, Yiran Chen

However, the high demand for memory capacity and computing power makes large-scale federated adversarial training infeasible on resource-constrained edge devices.

Adversarial Robustness Federated Learning +1

Automated Mobile Attention KPConv Networks via A Wide & Deep Predictor

no code implementations29 Sep 2021 Tunhou Zhang, Mingyuan Ma, Feng Yan, Hai Li, Yiran Chen

MAKPConv employs a depthwise kernel to reduce resource consumption and re-calibrates the contribution of kernel points towards each neighbor point via Neighbor-Kernel attention to improve representation power.

3D Point Cloud Classification Feature Engineering +2

AEGCN: An Autoencoder-Constrained Graph Convolutional Network

1 code implementation3 Jul 2020 Mingyuan Ma, Sen Na, Hongyu Wang

In extensive experiments on citation networks and other heterogeneous graphs, we demonstrate that adding autoencoder constraints significantly improves the performance of graph convolutional networks.

Decoder Graph Attention +1

Scalable Peaceman-Rachford Splitting Method with Proximal Terms

no code implementations14 Nov 2017 Sen Na, Mingyuan Ma, Mladen Kolar

Along with developing of Peaceman-Rachford Splittling Method (PRSM), many batch algorithms based on it have been studied very deeply.

Cannot find the paper you are looking for? You can Submit a new open access paper.