Writing study: SALART-VQA: Diagnosing Whether VLMs Understand Salient Artifacts in Generated Images

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Xiaoxiao Sun, Ruotian Zhang, Junzhe Huang, James Burgess, Serena Yeung-Levy · Official NeurIPS 2026 oral record

Observed writing choices, not acceptance rules. This study examines the inspected manuscript version. It does not establish why the paper was accepted or that its presentation choices should be copied unchanged.

Figure, table and section ledger

Editorial contribution type: Datasets, benchmarks & measurement (primary).

Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.

Canonical PDF

23 physical pages

Before references / appendix

≈ 9.24 page-equivalents

Main figures / tables

6 / 1

Attached appendix figures / tables

1 / 6

Attached appendix span

≈ 10.3 page-equivalents

Before references / appendix: ≈ 40.17%References / intervening material: ≈ 15.04%Attached appendix: ≈ 44.78%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

Section-by-section lengths and source pages

The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.

Top-level heading	Starts on PDF page	Estimated span	Share of entire PDF
1 Introduction	1	≈ 1.54 pp.	6.7%
2 Related work	3	≈ 0.46 pp.	2%
3 SALART-VQA Construction	3	≈ 2.05 pp.	8.91%
4 Experiments	5	≈ 4.09 pp.	17.78%
5 Conclusion	9	≈ 0.38 pp.	1.65%
References	10	≈ 3.47 pp.	15.09%
A Artifact taxonomy details	13	≈ 0.09 pp.	0.39%
B Image generation details	13	≈ 1.62 pp.	7.04%
C Prompt examples	15	≈ 0.3 pp.	1.3%
D Annotation process	15	≈ 0.85 pp.	3.7%
E VQA question design	16	≈ 3.13 pp.	13.61%
F Additional results	19	≈ 1.88 pp.	8.17%
G Broader impacts and ethics statement	21	≈ 0.24 pp.	1.04%
H Reproducibility statement	21	≈ 0.94 pp.	4.09%
I Limitations	22	≈ 0.34 pp.	1.48%
J Compute resources	23	≈ 0.91 pp.	3.96%

All detected figure and table locations

Main text

• Figure 1 · p. 2
• Figure 2 · p. 4
• Figure 3 · p. 5
• Table 1 · p. 6
• Figure 4 · p. 7
• Figure 5 · p. 8
• Figure 6 · p. 9

Attached appendix

• Table 2 · p. 14
• Table 3 · p. 15
• Figure 7 · p. 17
• Table 4 · p. 20
• Table 5 · p. 21
• Table 6 · p. 22
• Table 7 · p. 22

Argument and organization

1. Problem and contribution

   The opening separates detecting that an image contains an artifact from locating the right region and describing the supported defect. Figure 1 demonstrates a concrete case in which a correct yes/no answer coexists with incorrect grounding or explanation, motivating the four-question diagnostic chain.

2. Argument sequence

   The paper defines artifact and reference image groups, builds localized annotations and multiple-choice questions, then reports both joint success and question-level behavior. Paired references and a no-image control test alternative explanations such as indiscriminate artifact reporting or answer priors.

3. Evidence and verification

   Table 1 separates artifact/reference groups and all-question versus downstream-question success. Figure 4 explains which parts of the chain fail together; Figure 5 reports sensitivity versus reference-side calibration; Figure 6 tests image-free response priors. The prose correctly notes that high artifact recall is not equivalent to success on every grounded question.

Problem, claim and contribution

The opening separates detecting that an image contains an artifact from locating the right region and describing the supported defect. Figure 1 demonstrates a concrete case in which a correct yes/no answer coexists with incorrect grounding or explanation, motivating the four-question diagnostic chain.

Introduction and Figure 1, pp. 1–3, especially p. 2 · Main paper

Argument and section order

The paper defines artifact and reference image groups, builds localized annotations and multiple-choice questions, then reports both joint success and question-level behavior. Paired references and a no-image control test alternative explanations such as indiscriminate artifact reporting or answer priors.

Benchmark construction §3, pp. 3–5; main results pp. 6–8; no-image control Figure 6, p. 9 · Main paper

Figures, captions and visual explanation

Figure 1 aligns the image, model responses and diagnostic questions so the reader can see the mismatch between presence detection and grounded understanding. Figure 4 places per-question bars beside a heatmap of four-bit correctness patterns; the same model ordering links marginal accuracy to joint error structure, and the caption defines 1111 and 0000 explicitly.

Figure 1, p. 2; Figure 4, p. 7; rendered pages 2 and 7 · Main paper

Tables, comparisons and evidence

Table 1 separates artifact/reference groups and all-question versus downstream-question success. Figure 4 explains which parts of the chain fail together; Figure 5 reports sensitivity versus reference-side calibration; Figure 6 tests image-free response priors. The prose correctly notes that high artifact recall is not equivalent to success on every grounded question.

Table 1, p. 6; Figures 4–6 and §§4.1.1–4.2, pp. 7–9 · Main paper

Appendix and reproducibility

The appendix provides artifact definitions, generation/inpainting procedures, exact question prompts and scoring conditions, then disaggregates source/type results. Limitations restrict interpretation to salient, localized and describable defects rather than the prevalence of all artifacts in unconstrained generated imagery.

Appendices A–E, pp. 13–19; Appendix F, pp. 20–22; Appendices G–J, pp. 21–23 · Main paper

Clarity and writing conventions

Bold analytical lead sentences name a finding before the supporting numbers, such as distinguishing artifact recall from full understanding. The source also illustrates why model labels need a consistency pass: the introductory response example names different model revisions than the representative quantitative plot, so a guide should not silently equate those panels.

Figure 1 model labels, p. 2; Figure 4 labels and §4.1.1 lead sentences, p. 7 · Main paper

What to reuse—and what not to infer

Transferable lesson: If a task has a chain of subclaims, include a motivating counterexample, marginal metrics, joint correctness patterns, paired negative controls and an input-removal test rather than one aggregate accuracy.

Boundary: All-four-question success is a joint image-level event, not the mean of four accuracies. This controlled salient-defect benchmark does not measure artifact prevalence or all possible failures in unconstrained images; the public version is not a verified accepted revision.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked

2026-10-02

Reading status

Writing-focused manuscript scan + selected visuals inspected

Main text

Writing-oriented scan across manuscript framing, section sequence, figure/table captions, selected argument/evaluation prose and conclusion; not exhaustive technical or proof verification. Sections 1–5, pp. 1–9; references pp. 10–13. Rendered the motivation/question-chain example p. 2 and per-question/failure-pattern diagnostic plot p. 7. Source is the exact public author version listed below, not a verified accepted/camera-ready revision.

Appendix / supplement

Writing-oriented appendix/documentation scan: Appendices A–J, pp. 13–23: artifact definitions, image generation, prompts, annotation, scoring, subgroup results, ethics, reproducibility, limitations and compute. Source code, data, model outputs and external video assets were not executed or independently validated.

Visually inspected PDF pages

2, 7

This is a writing-focused scan of the manuscript and the stated supplementary scope: framing, organization, visual explanation, evidence presentation and wording. It is not a line-by-line proof audit, reproduction of results or exhaustive scientific review.

• Public author arXiv manuscript 2606.12671v1; not verified identical to the accepted or camera-ready OpenReview revision · 23 pages