Author

Pei-Yu Zang

h-index 5 View on Semantic Scholar

We have 6 of 15 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Aug 2026

SubZero+: Memory-Efficient Adaptive Zeroth-Order LLM Fine-Tuning in Random Subspaces

Zeroth-order (ZO) optimization with SGD in random subspaces enables memory-efficient fine-tuning of large language models without backpropagation. However, high gradient estimation noise fundamentally undermines adaptive optimizers like Adam. We propose SubZero+, which achieves practical adaptive ZO optimization throug...

Zi-Ming Yu, Shu-Yao Xiao, Xingyu Zhao et al. · 0 citations

#artificial intelligence Preprint Sep 2026

FromPitch2Board: Benchmarking LLM Agents in Long-Horizon Football Management

FromPitch2Board, a deterministic football-management benchmark that studies five configurable factors through controlled comparisons on a single simulator, is introduced, showing that responsibility scope and horizon expose behavior changes that a single headline score conceals.

Pei-Yu Zang · 0 citations

Jul 2026

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

FlashPDE provides a hardware-efficient execution layer that bridges differentiable PDE solvers and GPU-optimized numerical computation within the PyTorch ecosystem, while maintaining numerical agreement with PyTorch finite-difference references.

Pei-Yu Zang, Bosen Xie, Ruoxi Xu et al. · arXiv.org · 1 citation

Preprint Jul 2026

KernelGenBench: Can LLMs and Agents Write Efficient Kernels Across Operator Sources and Hardware Platforms?

KernelGenBench is presented, the first unified multi-source and multi-chip infrastructure for evaluating LLM- and agent-generated Triton kernels and establishes operator source, hardware platform, and agentic scaffold as distinct dimensions of kernel-generation capability, and shows that success in a familiar source-ha...

Pei-Yu Zang, Jian-Hang Tao, Jia-Ling Zhang et al. · 0 citations

Jul 2026

KernelGenBench: A Multi-Source and Multi-Chip Benchmark for LLM-based Kernel Generation

It is shown that agent-based methods consistently outperform pure LLM sampling methods, while cuBLAS operators are the most challenging across all methods, and a unified benchmark for systematically evaluating LLM-and agent-generated Triton kernels across diverse operator sources and heterogeneous hardware platforms is...

Pei-Yu Zang, Jian-Hang Tao, Jia-Ling Zhang et al. · arXiv.org · 2 citations · ⚡1

#machine learning Preprint Aug 2026

SubZero+: Efficient Zeroth-Order LLM Fine-Tuning via Large Learning Rates

Experiments show that SubZero+, an improved SubZero framework that improves stability in three complementary ways, consistently outperforms prior ZO baselines, enlarges the stable learning-rate range, and narrows the gap to first-order methods with minimal extra memory overhead.

Ziming Yu, Shu-Yao Xiao, Xingyu Zhao et al. · 0 citations