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researcher

Quan Yuan

4 papers hereh-index 67k citations23 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CL1
  • cs.DC1
  • cs.LG1
same name
  • Quan Yuan — 6 papers, h 8
  • Quan Yuan — 4 papers, h 4
  • Quan Yuan — 3 papers, h 2
  • Quan Yuan — 3 papers, h 2
  • Quan Yuan — 2 papers, h 1
  • Quan Yuan — 2 papers, h 18

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.DC2026

Searching for Plans You Can Actually Build: A Realizability-Aware Full-Space Optimizer for MoE Training and Serving

Quan Yuan, Jie Zhao

Mixture-of-Experts (MoE) systems split a program's plan space in two: the space a cost model can rank, and the smaller space a real toolchain can actually build. Automatic optimize…

cs.AI2025

AKG kernel Agent: A Multi-Agent Framework for Cross-Platform Kernel Synthesis

Jinye Du, Quan Yuan, Zuyao Zhang +16

Modern AI models demand high-performance computation kernels. The growing complexity of LLMs, multimodal architectures, and recommendation systems, combined with techniques like sp…

cs.CL2025

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431

In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…

cs.LG2025

Probing In-Context Learning: Impact of Task Complexity and Model Architecture on Generalization and Efficiency

Binwen Liu, Peiyu Xu, Quan Yuan +1

We investigate in-context learning (ICL) through a meticulous experimental framework that systematically varies task complexity and model architecture. Extending beyond the linear…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.