3 citations · 5 across the 13 of their papers we have counts for
8 papers · 1 filter
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…