Author

Yuhan Liu

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Preprint Aug 2026

GraphIR: Architecture-Level Search States for LLM-Guided Neural Architecture Evolution

GraphIR, an architecture-aware intermediate representation that supplements executable programs with a mutation-aligned candidate state, achieves the best overall search performance while maintaining comparable model size and favorable end-to-end NAS efficiency when integrated into OpenEvolve.

Zhen Liu, Wanqi Zhou, Shuanghao Bai et al. · 1 citation

#computer vision Preprint Aug 2026

An AI4AI Framework for Visual Token Pruning

This paper argues that the key lies in designing an appropriate search-state representation that connects the internal knowledge of LLMs with the structural requirements and constraints of visual-token pruning, and proposes AutoPrune, a training-free framework for LLM-driven visual-token pruning policy design.

Zhen Liu, Wenli Huang, Wei Song et al. · 0 citations

Preprint Jul 2026

Overcoming the Weakest-Link Effect in LLM-Driven Program Optimization via Heterogeneous Edit Recombination

HELP, a program optimizer that prompts an LLM to generate diverse, non-overlapping atomic edits and then systematically selects and composes them into coherent program improvements using evaluator scores, is introduced.

Jingwen Fu, Zhen Liu, Yuhan Liu et al. · 2 citations