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ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code — arXiv:2609.38642

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.38642
License (as archived): CC0-1.0
Archived: 2026-10-07T12:41:59.851Z
SHA-256 of the archived text: 3758a06c9d3fded9705a473ec1a8d8f5cd827ff49c91fffc70737df204d44c2d
Stable URL of this page: https://metraipolis.com/documento/dc_424ddd9addfa

How to cite

ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code — arXiv:2609.38642 — arXiv (en), https://arxiv.org/abs/2609.38642 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_424ddd9addfa (Metraipolis archive dc_424ddd9addfa, sha256 3758a06c9d3fded9705a473ec1a8d8f5cd827ff49c91fffc70737df204d44c2d)

BibTeX

@misc{dc424ddd9addfa,
  title = {ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code — arXiv:2609.38642},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.38642},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_424ddd9addfa; sha256 3758a06c9d3fded9705a473ec1a8d8f5cd827ff49c91fffc70737df204d44c2d},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.38642. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and without altering unrelated content. Existing benchmarks emphasize either code executability or chart quality, but their metrics do not clearly distinguish request completion from missed coupled updates and gratuitous changes. We introduce ChartRevise, a structured dataset and evaluation protocol for exact program-grounded chart editing. For dataset construction, we build on the grammar of graphics to systematically cover chart-editing operations, using source-program checks to verify their applicability across chart types and libraries. To improve edit exactness, our pipeline checks individual requirements and guides repair or exclusion when they are unmet. The resulting dataset contains 92,438 records covering 344 edit types across 20 chart types and three plotting libraries. For evaluation, our reference-free protocol separately measures atomic requirement completion, identifies gratuitous changes, and detects missed coupled updates. These checks are combined with successful execution and rendering to determine exact-edit success. Across five models and four external benchmarks, fine-tuning yields relative gains of 16\% in mean requirement recall and 22\% in mean exact-edit rate.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-10-01 in cs.AI).
Categorie arXiv: Artificial Intelligence (cs.AI) ; Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2609.38642 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T12:14:13.654Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-10-01?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).