3 citations · 5 across the 13 of their papers we have counts for
14 papers
Top-Down Microarchitecture Analysis Without Causal Modelling Is Dangerous!
Chenxi Wang, Lei Wang, Wanling Gao +3
Top-Down Microarchitecture Analysis (TMA) is the standard for identifying CPU bottlenecks. However, TMA implicitly models performance via a single causal path: Workload(dataset, al…
SmartANN: Object Causal Modeling Boosts Approximate Nearest Neighbor Diagnosis and Auto-Design
Yutong Zhou, Guoxin Kang, Lei Wang +3
Approximate Nearest Neighbor (ANN) algorithms achieve high efficiency through interdependent phases across index construction and query execution. This coupling allows upstream per…
When AI Designs AI: Innovation or Imitation?
Yikang Yang, Zhengxin Yang, Luzhou Peng +4
Recent advances in LLM agents have made them increasingly capable of designing methods for complex AI tasks. This raises two central questions about agent-designed methods relative…
Inference of Component Effect on System Performance
Chenxi Wang, Lei Wang, Wanling Gao +5
In a computer system, multiple components--such as the CPU, memory, and others--work together as a system whose performance can be directly measured. However, the effect of a compo…
CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models
Xiaorui Wang, Fanda Fan, Chenxi Wang +9
Recent progress in time-series forecasting has led to rapidly increasing architectural complexity, yet many reported State-of-the-Art gains are statistically fragile or misattribut…
Probing Memes in LLMs: A Paradigm for the Entangled Evaluation World
Luzhou Peng, Zhengxin Yang, Honglu Ji +6
Current evaluation paradigms for large language models (LLMs) characterize models and datasets separately, yielding coarse descriptions: items in datasets are treated as pre-labele…
GraDE: A Graph Diffusion Estimator for Frequent Subgraph Discovery in Neural Architectures
Yikang Yang, Zhengxin Yang, Minghao Luo +5
Finding frequently occurring subgraph patterns or network motifs in neural architectures is crucial for optimizing efficiency, accelerating design, and uncovering structural insigh…
On Meta-Evaluation
Hongxiao Li, Chenxi Wang, Fanda Fan +4
Evaluation is the foundation of empirical science, yet the evaluation of evaluation itself -- so-called meta-evaluation -- remains strikingly underdeveloped. While methods such as…
KAIROS: Unified Training for Universal Non-Autoregressive Time Series Forecasting
Kuiye Ding, Fanda Fan, Zheya Wang +5
In the World Wide Web, reliable time series forecasts provide the forward-looking signals that drive resource planning, cache placement, and anomaly response, enabling platforms to…
TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding
Kuiye Ding, Fanda Fan, Chunyi Hou +4
Multivariate time series forecasting is essential in domains such as finance, transportation, climate, and energy. However, existing patch-based methods typically adopt fixed-lengt…
Achieving Consistent and Comparable CPU Evaluation
Chenxi Wang, Lei Wang, Wanling Gao +5
The challenge of CPU evaluation lies in the fact that user-perceived performance metrics can only be measured on an independently running system consisting of the CPU and other ind…
Could Bibliometrics Reveal Top Science and Technology Achievements and Researchers? The Case for Evaluatology-based Science and Technology Evaluation
Guoxin Kang, Wanling Gao, Lei Wang +5
By utilizing statistical methods to analyze bibliographic data, bibliometrics faces inherent limitations in identifying the most significant science and technology achievements and…
Bridging the Gap Between Domain-specific Frameworks and Multiple Hardware Devices
Xu Wen, Wanling Gao, Lei Wang +1
The rapid development of domain-specific frameworks has presented us with a significant challenge: The current approach of implementing solutions on a case-by-case basis incurs a t…
Precise, Scalable and Online Request Tracing for Multi-tier Services of Black Boxes
Bo Sang, Jianfeng Zhan, Zhihong Zhang +4
As more and more multi-tier services are developed from commercial off-the-shelf components or heterogeneous middleware without source code available, both developers and administr…