From the 1 of 5 linked papers with an AI index.
5 papers
MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems
Xinle Deng, Ruobin Zhong, Hujin Peng +15
The paper introduces MemTrace, a framework that converts large language model memory pipelines into executable graphs to trace and attribute errors, and provides a benchmark (MemTr…
Learning When to Optimize: Verified Optimization Skills from Expert GPU-Kernel Lineages
Shuoming Zhang, Qiuchu Yu, Yangyu Zhang +6
LLM-based agents are increasingly used to generate GPU kernels, but they often know what optimizations to try without knowing when those optimizations are sound. We introduce KLine…
Scalable Clifford-Based Classical Initialization for the Quantum Approximate Optimization Algorithm
Dhanvi Bharadwaj, Yuewen Hou, Guang-Yi Li +1
Variational Quantum Algorithms (VQAs), such as the Quantum Approximate Optimization Algorithm (QAOA), offer a promising route to tackling combinatorial optimization problems on nea…
HiFloat4 Format for Language Model Inference
Yuanyong Luo, Jing Huang, Yu Cheng +19
This paper introduces HiFloat4 (HiF4), a block floating-point data format tailored for deep learning. Each HiF4 unit packs 64 4-bit elements with 32 bits of shared scaling metadata…
M2XFP: A Metadata-Augmented Microscaling Data Format for Efficient Low-bit Quantization
Weiming Hu, Zihan Zhang, Haoyan Zhang +8
Existing low-bit Microscaling (MX) formats, such as MXFP4, often suffer from substantial accuracy degradation due to the use of a shared scaling factor with the Power-of-Two format…