arXiv:2606. 10334v1 Announce Type: new Abstract: Code-generating large language models (LLMs) increasingly produce visual artifacts such as charts, web pages, and slides by writing programs that are executed by non-differentiable renderers, committing to code before observing the render.
By Haoyu Dong
arXiv:2606. 00188v1 Announce Type: cross Abstract: While current multimodal models are proficient at open-ended visual editing, executing precise single-answer edits remains an important obstacle.
By Kai Xu, Ellis Brown, Shrikar Madhu, Rob Fergus, He He, Saining Xie
arXiv:2512. 03042v3 Announce Type: replace-cross Abstract: We introduce PPTArena, a benchmark for PowerPoint editing that evaluates how agents modify real slides from natural-language instructions.
By Michael Ofengenden, Yunze Man, Ziqi Pang, Liang-Yan Gui, Yu-Xiong Wang
arXiv:2606. 15693v1 Announce Type: cross Abstract: LLMs have significantly advanced code generation, enabling the synthesis of functional programs.
By Charly Reux (UR, INSA Rennes, DiverSe), Mathieu Acher (CNRS, IUF, IRISA, UR, DiverSe), Djamel Eddine Khelladi (DiverSe, UR, CNRS, IRISA), Cl\'ement Quinton (SPIRALS, CNRS), Olivier Barais (UR, IRISA, DiverSe)
arXiv:2602. 18548v2 Announce Type: replace-cross Abstract: Design-to-code translates high-fidelity UI designs into executable front-end implementations, but progress remains hard to compare due to inconsistent datasets, toolchains, and evaluation protocols.
By Qiao Xu, Yipeng Yu, Chengxiao Feng, Xu Liu
arXiv:2606. 08415v1 Announce Type: cross Abstract: While recent text-guided video editing models excel at elementary tasks (e.
By Jiangtao Wu, Jiaming Wang, Yiwen He, Yuanxing Zhang, Shihao Li, Dunyuan Liu, Xuedong Zhao, Jialu Chen, Zekun Moore Wang, Jiaheng Liu
arXiv:2607. 15272v1 Announce Type: cross Abstract: Editing the figures in a research paper is a routine and time-consuming part of everyday research practice: authors relabel components, rearrange panels, and restyle visuals as they revise their manuscripts.
By Yasheng Sun, Zezi Zeng, Yifan Yang, Chong Luo, Wenyi Wang, Ziwei Liu, J\"urgen Schmidhuber
arXiv:2607. 05310v1 Announce Type: new Abstract: Model editing promises a fast, targeted way to correct post-deployment mistakes in medical vision-language models (VLMs) without costly retraining.
By Guli Zhu, Chenwei Wu, Liyue Shen
arXiv:2601. 04390v2 Announce Type: replace Abstract: High-quality methodology figures are central to scientific communication, yet they remain difficult and time-consuming to create.
By Siyuan Huang, Yifan Zhou, Yutong Gao, Zi Yin, Juyang Bai, Xinxin Liu, Rama Chellappa, Chun Pong Lau, Cheng Peng, Sayan Nag, Shraman Pramanick
arXiv:2608. 12611v1 Announce Type: cross Abstract: Existing screenshot-to-code systems face a trade-off between flexibility and controllability.
By Houston H. Zhang, Tao Zhang, Li Gu, Linfeng Ye, Yuanhao Yu, Xinxin Zuo, Yang Wang, Zhixiang Chi
Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-Pro and GPT-Image-2 demonstrate emerging capabilities in multi-source image editing (MIE), including tasks such as object synthesis, person-background composition, and cross-image style fusion.
arXiv:2605. 10873v2 Announce Type: replace-cross Abstract: Recovering editable CAD programs from images or 3D observations is central to AI-assisted design, but progress is difficult to measure because existing evaluations are fragmented across datasets, modalities, and metrics.
By Anna C. Doris, Jacob Thomas Sony, Ghadi Nehme, Era Syla, Amin Heyrani Nobari, Faez Ahmed