Titlebook: Benchmarking, Measuring, and Optimizing; 15th BenchCouncil In Sascha Hunold,Biwei Xie,Kai Shu Conference proceedings 2024 The Editor(s) (if

EXTOL

,AGIBench: A Multi-granularity, Multimodal, Human-Referenced, Auto-Scoring Benchmark for Large Langunced, and auto-scoring benchmarking methodology for LLMs. Instead of a collection of blended questions, AGIBench focuses on three typical ability branches and adopts a four-tuple to label the attributes of each question. First, it supports multi-granula

中国纪念碑

,Automated HPC Workload Generation Combining Statistical Modeling and Autoregressive Analysis,rocesses. In our proposed approach, job arrivals will be generated by a statistical model that consists of multiple Poisson processes with constraints provided by Gamma distribution. Then, we perform autoregressive analysis on the changing trends of job attributes to extract sequence information fro

MOAN

,Hmem: A Holistic Memory Performance Metric for Cloud Computing,ns. To reflect the overall performance of a given workload, we calculate the correlation between our proposed metric and the workload’s throughput. Experimental results show that Hmem exhibits an average improvement of 70% on correlation coefficients compared to state-of-the-art memory performance m

萤火虫

滋养

BLANC

Titus L. Daniels,Thomas R. Talbotdels, graph-based models, and pre-trained models. The purpose of the work is to establish a fair and reliable benchmark for future innovation in the field of molecular property prediction, emphasizing the importance of multidimensional perspectives.