2 citations · 4 across the 10 of their papers we have counts for
12 papers
Fengshui: Demystifying Chiplet Ecosystem and Bespoke Neural Network Accelerator Codesign
Haoran Jin, Jirong Yang, Zhiheng Zhang +5
Modern ML workloads, with stringent latency and energy constraints, are increasingly hard to run efficiently on homogeneous commodity hardware. We argue that operator-level disaggr…
Rethinking Infrared Small Target Detection: A Foundation-Driven Efficient Paradigm
Chuang Yu, Jinmiao Zhao, Yunpeng Liu +6
While large-scale visual foundation models (VFMs) exhibit strong generalization across diverse visual domains, their potential for single-frame infrared small target (SIRST) detect…
MIND: Multi-rationale INtegrated Discriminative Reasoning Framework for Multi-modal Large Models
Chuang Yu, Jinmiao Zhao, Mingxuan Zhao +5
Recently, multimodal large language models (MLLMs) have been widely applied to reasoning tasks. However, they suffer from limited multi-rationale semantic modeling, insufficient lo…
Mozart: A Chiplet Ecosystem-Accelerator Codesign Framework for Composable Bespoke Application Specific Integrated Circuits
Haoran Jin, Jirong Yang, Yunpeng Liu +3
Modern AI acceleration faces a fundamental challenge: conventional assumptions about memory requirements, batching effectiveness, and latency-throughput tradeoffs are systemwide ge…
SpikeSTAG: Spatial-Temporal Forecasting via GNN-SNN Collaboration
Bang Hu, Changze Lv, Mingjie Li +5
Spiking neural networks (SNNs), inspired by the spiking behavior of biological neurons, offer a distinctive approach for capturing the complexities of temporal data. However, their…
Enhancing Social Media Rumor Detection: A Semantic and Graph Neural Network Approach for the 2024 Global Election
Liu Yan, Liu Yunpeng, Zhao Liang
The development of social media platforms has revolutionized the speed and manner in which information is disseminated, leading to both beneficial and detrimental effects on societ…
Why and How: Knowledge-Guided Learning for Cross-Spectral Image Patch Matching
Chuang Yu, Yunpeng Liu, Jinmiao Zhao +1
Recently, cross-spectral image patch matching based on feature relation learning has attracted extensive attention. However, performance bottleneck problems have gradually emerged…
From Easy to Hard: Progressive Active Learning Framework for Infrared Small Target Detection with Single Point Supervision
Chuang Yu, Jinmiao Zhao, Yunpeng Liu +3
Recently, single-frame infrared small target (SIRST) detection with single point supervision has drawn wide-spread attention. However, the latest label evolution with single point…
LR-Net: A Lightweight and Robust Network for Infrared Small Target Detection
Chuang Yu, Yunpeng Liu, Jinmiao Zhao +1
Limited by equipment limitations and the lack of target intrinsic features, existing infrared small target detection methods have difficulty meeting actual comprehensive performanc…
Refined Infrared Small Target Detection Scheme with Single-Point Supervision
Jinmiao Zhao, Zelin Shi, Chuang Yu +1
Recently, infrared small target detection with single-point supervision has attracted extensive attention. However, the detection accuracy of existing methods has difficulty meetin…
Towards Robust Infrared Small Target Detection: A Feature-Enhanced and Sensitivity-Tunable Framework
Jinmiao Zhao, Zelin Shi, Chuang Yu +2
Recently, single-frame infrared small target (SIRST) detection technology has attracted widespread attention. Different from most existing deep learning-based methods that focus on…
Multi-Scale Direction-Aware Network for Infrared Small Target Detection
Jinmiao Zhao, Zelin Shi, Chuang Yu +3
Infrared small target detection faces the problem that it is difficult to effectively separate the background and the target. Existing deep learning-based methods focus on edge and…