mlsanityData to 14 Oct 2026

Pixels or Code? Benchmarking Instruction-Guided Visual Artifact Operation

arXiv 2610.16444 ↗First posted 12 Oct 2026cs.CVcited by 0

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Abstract (arXiv)

Visual artifacts such as charts, technical diagrams, webpages, and document pages underpin scientific, commercial, and engineering workflows. Editing these artifacts requires direct modification, dependency-aware updates, preservation of unaffected content, and compliance with domain constraints. We define this capability as Visual Artifact Operation (VAO). Prior benchmarks test parts of this problem, including cascading updates in charts. We study direct edits, dependent updates, and preservation across visual domains and pixel, code, and agent paradigms under one image-only protocol. We introduce Visual Artifact Operation Bench (VAO-Bench), comprising 1,573 manually screened tasks across nine artifact categories and three difficulty levels. VAO-Bench uses executable artifacts and deterministic rendering to trace reference transformations and annotate direct edits, dependent updates, and preservation constraints. All systems receive the same source image and instruction; we evaluate pixel-space editors, code-generating multimodal systems, and tool-using agents on direct-edit accuracy, dependency-aware update, content preservation, domain validity, and visual quality. Experiments show that executable-code systems better support dependent updates, while pixel-space editors offer faster execution and strong visual quality. Explicitly stating dependencies improves both paradigms, identifying implicit-update inference as a central bottleneck. VAO-Bench provides a reproducible foundation for dependable visual artifact editing across generation paradigms.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 25 of its 34 references that are in the map. First posted on arXiv 12 Oct 2026.

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25 of 34 references.

References · 25

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  2. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  3. 2023MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editingcited by 624
  4. 2022Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpaintingcited by 233
  5. 2025ImgEdit: A Unified Image Editing Dataset and Benchmarkcited by 231
  6. 2024Design2Code: Benchmarking Multimodal Code Generation for Automated Front-End Engineeringcited by 152
  7. 2024ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generationcited by 129
  8. 2024I2EBench: A Comprehensive Benchmark for Instruction-based Image Editingcited by 63
  9. 2025DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generationcited by 45
  10. 2025ChartEdit: How Far Are MLLMs From Automating Chart Analysis? Evaluating MLLMs' Capability via Chart Editingcited by 32
  11. 2025LMM4Edit: Benchmarking and Evaluating Multimodal Image Editing with LMMscited by 24
  12. 2025ComplexBench-Edit: Benchmarking Complex Instruction-Driven Image Editing via Compositional Dependenciescited by 21
13 more
  1. 2025Factuality Matters: When Image Generation and Editing Meet Structured Visualscited by 20
  2. 2025CompBench: Benchmarking Complex Instruction-guided Image Editingcited by 17
  3. 2025WebGen-Agent: Enhancing Interactive Website Generation with Multi-Level Feedback and Step-Level Reinforcement Learningcited by 15
  4. 2025SVGEditBench V2: A Benchmark for Instruction-based SVG Editingcited by 11
  5. 2025Charts Are Not Images: On the Challenges of Scientific Chart Editingcited by 11
  6. 2025Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editingcited by 10
  7. 2026ChartEditBench: Evaluating Grounded Multi-Turn Chart Editing in Multimodal Language Modelscited by 8
  8. 2026GRADE: Benchmarking Discipline-Informed Reasoning in Image Editingcited by 7
  9. 2026ChartSync: A Benchmark for Visuo-Logical Cascading Chart Editingcited by 4
  10. 2026VisEditBench: Can Vision-Language Models Edit Visualization Code from Multimodal Feedback?cited by 4
  11. 2026SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisionscited by 2
  12. 2026Edit2TikZ: A Comprehensive and Challenging Benchmark for Scientific Figure Editing with TikZcited by 1
  13. 2026EdiTikZ: Scientific Figure Editing from Revision Trajectoriescited by 1

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