419 citations · 682 across the 54 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…
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…
AutoMatBench: An Automatic Optimization Toolkit for the Acceleration of Material Properties Prediction Benchmarking
Hongxiao Li, Wanling Gao
Material property prediction (MPP) infers key properties from chemical composition and structure, accelerating the discovery and optimization of novel materials. In the realm of MP…
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…