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Author

Yepeng Liu

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#artificial intelligence Preprint Sep 2026

Figures as Programs: Recursive Generation of Editable Scientific Figures

Examination of the proposed FigTree system produces high-quality figures, while also enabling more effective editing than existing raster-based methods, and proposes a multi-agent system that automatically transforms a scientific paper into a structured vector figure.

Yepeng Liu, Da-Sen Dai, Cheng-Zhi Liu et al. · 2 citations
#artificial intelligence Preprint Aug 2026

Learning to Follow In-Context Watermark Instructions via Self-Distillation

This work proposes a self-contained two-stage training method, requiring no distillation from a stronger model, no manual annotation, and no pre-existing ICW IF ability, and introduces $\mathsf{ICWBench}$, a benchmark of three verifiable ICW instruction families, each scored on both detectability and answer quality.

Yepeng Liu, Tian-Yi Chen, Xuandong Zhao et al. · 0 citations

Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs

This work introduces a novel approach, \textit{CanaryTrace}, to safeguard the ownership of text datasets and effectively detect unauthorized use by RA-LLMs, and demonstrates high query efficiency, detectability, and consistency, along with minimal perturbation to the original dataset, all without compromising the perfo...

Yepeng Liu, Xuandong Zhao, D. Song et al. · 15 citations · ⚡1

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