3 papers
cs.CL2026
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…
cs.LG2026
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…
cs.PF2025
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…