5 citations · 8 across the 16 of their papers we have counts for
16 papers
BigPower: Hierarchical Source-Level Module Power Estimation for CPUs with Large Language Models
Honghua Zhu, Chunjie Luo, Jianfeng Zhan
Accurate power estimation is important for understanding and optimizing CPU power behavior, yet practical workflows often rely on simulation-derived information or post-silicon ana…
DualSG: A Dual-Stream Explicit Semantic-Guided Multivariate Time Series Forecasting Framework
Kuiye Ding, Fanda Fan, Yao Wang +6
Multivariate Time Series Forecasting plays a key role in many applications. Recent works have explored using Large Language Models for MTSF to take advantage of their reasoning abi…
Quantifying the Dynamics of Harm Caused by Retracted Research
Yunyou Huang, Jiahui Zhao, Dandan Cui +10
Despite enormous efforts devoted to understand the characteristics and impacts of retracted papers, little is known about the mechanisms underlying the dynamics of their harm and t…
Establishing Rigorous and Cost-effective Clinical Trials for Artificial Intelligence Models
Wanling Gao, Yunyou Huang, Dandan Cui +22
A profound gap persists between artificial intelligence (AI) and clinical practice in medicine, primarily due to the lack of rigorous and cost-effective evaluation methodologies. S…
AI.vs.Clinician: Unveiling Intricate Interactions Between AI and Clinicians through an Open-Access Database
Wanling Gao, Yuan Liu, Zhuoming Yu +21
Artificial Intelligence (AI) plays a crucial role in medical field and has the potential to revolutionize healthcare practices. However, the success of AI models and their impacts…
Younger: The First Dataset for Artificial Intelligence-Generated Neural Network Architecture
Zhengxin Yang, Wanling Gao, Luzhou Peng +3
Designing and optimizing neural network architectures typically requires extensive expertise, starting with handcrafted designs and then manual or automated refinement. This depend…
Evaluatology: The Science and Engineering of Evaluation
Jianfeng Zhan, Lei Wang, Wanling Gao +10
Evaluation is a crucial aspect of human existence and plays a vital role in various fields. However, it is often approached in an empirical and ad-hoc manner, lacking consensus on…
AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AI
Fanda Fan, Chunjie Luo, Wanling Gao +1
The burgeoning field of Artificial Intelligence Generated Content (AIGC) is witnessing rapid advancements, particularly in video generation. This paper introduces AIGCBench, a pion…
SAIBench: A Structural Interpretation of AI for Science Through Benchmarks
Yatao Li, Jianfeng Zhan
Artificial Intelligence for Science (AI4S) is an emerging research field that utilizes machine learning advancements to tackle complex scientific computational issues, aiming to en…
Hierarchical Masked 3D Diffusion Model for Video Outpainting
Fanda Fan, Chaoxu Guo, Litong Gong +5
Video outpainting aims to adequately complete missing areas at the edges of video frames. Compared to image outpainting, it presents an additional challenge as the model should mai…
OpenClinicalAI: An Open and Dynamic Model for Alzheimer's Disease Diagnosis
Yunyou Huang, Xiaoshuang Liang, Xiangjiang Lu +9
Although Alzheimer's disease (AD) cannot be reversed or cured, timely diagnosis can significantly reduce the burden of treatment and care. Current research on AD diagnosis models u…
OpenAPMax: Abnormal Patterns-based Model for Real-World Alzheimer's Disease Diagnosis
Yunyou Huang, Xianglong Guan, Xiangjiang Lu +8
Alzheimer's disease (AD) cannot be reversed, but early diagnosis will significantly benefit patients' medical treatment and care. In recent works, AD diagnosis has the primary assu…
WPC: Whole-picture Workload Characterization
Lei Wang, Kaiyong Yang, Chenxi Wang +7
This article raises an important and challenging workload characterization issue: can we uncover each critical component across the stacks contributing what percentages to any spec…
Quality at the Tail of Machine Learning Inference
Zhengxin Yang, Wanling Gao, Chunjie Luo +4
Machine learning inference should be subject to stringent inference time constraints while ensuring high inference quality, especially in safety-critical (e.g., autonomous driving)…
High fusion computers: The IoTs, edges, data centers, and humans-in-the-loop as a computer
Wanling Gao, Lei Wang, Mingyu Chen +13
Emerging and future applications rely heavily upon systems consisting of Internet of Things (IoT), edges, data centers, and humans-in-the-loop. Significantly different from warehou…
OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings
Yunyou Huang, Nana Wang, Suqin Tang +10
This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of s…