Writing study: VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments

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← CVPR 2026 oral writing corpus

Zelai Xu, Zhexuan Xu, Xiangmin Yi, Huining Yuan, Mo Guang, Kaiwen Long, Xinlei Chen, Yi Wu, Chao Yu, Yu Wang · Official CVPR 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

12 physical pages

Before references / appendix

≈ 8.1 page-equivalents

Main figures / tables

6 / 4

Attached appendix figures / tables

0 / 0

Attached appendix span

Separate file recorded below; not in this PDF total

Before references / appendix: ≈ 67.5%References / intervening material: ≈ 32.5%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

Extraction notes: No attached appendix boundary detected. Zero means no recognized caption, not independently verified absence.

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	≈ 1.48 pp.	12.33%
2. VS-BENCH environments	3	≈ 1.3 pp.	10.83%
3. Evaluating VLMs in VS-BENCH	4	≈ 1.73 pp.	14.42%
4. Analysis	6	≈ 1.86 pp.	15.5%
5. Related work	8	≈ 0.55 pp.	4.58%
6. Conclusion	8	≈ 0.28 pp.	2.33%
References	9	≈ 3.9 pp.	32.5%

All detected figure and table locations

Main text

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

Attached appendix

No recognized caption labels.

Separate source files—excluded from canonical-PDF totals

A separate author version may repeat main text and references. Whole-file lengths and counts are not extra appendix material and are never added to the canonical PDF totals. Read the study's source scope for which sections received substantive reading versus layout inspection.

Additional source 1

Separate PDF (or ZIP containing it): whole-file layout of 24 physical pages; 23 detected figures and 7 tables. These may include overlapping main-text material.

Located appendix only: starts on physical p.1; ≈ 23.91 page-equivalents, 23 figure labels and 7 table labels. This interval is distinct from the whole file.

Detected heading	PDF page	Estimated span
A. Ethics statement	1	≈ 0.41 pp.
B. Limitations	1	≈ 0.15 pp.
C. Models configuration details	1	≈ 0.13 pp.
D. Perception evaluation details	1	≈ 4.45 pp.
E. Strategic reasoning evaluation details	6	≈ 2.09 pp.
F. Decision-making evaluation details	8	≈ 3.77 pp.
G. Additional experiment results	12	≈ 3.57 pp.
H. Failure case examples	15	≈ 2.12 pp.
I. Additional environments	17	≈ 2.07 pp.
J. Environment details	19	≈ 4.29 pp.
K. Use of LLMs	24	≈ 0.87 pp.

• Table 5 · p. 2
• Figure 7 · p. 2
• Figure 8 · p. 2
• Figure 9 · p. 3
• Figure 10 · p. 3
• Figure 11 · p. 4
• Figure 12 · p. 4
• Figure 13 · p. 4
• Figure 14 · p. 4
• Figure 15 · p. 5
• Figure 16 · p. 5
• Figure 17 · p. 5
• Figure 18 · p. 5
• Table 6 · p. 11
• Table 7 · p. 12
• Table 8 · p. 12
• Figure 19 · p. 14
• Table 9 · p. 15
• Table 10 · p. 15
• Figure 21 · p. 15
• Table 11 · p. 16
• Figure 20 · p. 16
• Figure 22 · p. 17
• Figure 23 · p. 18
• Figure 24 · p. 18
• Figure 25 · p. 18
• Figure 26 · p. 19
• Figure 27 · p. 19
• Figure 28 · p. 19
• Figure 29 · p. 19

Argument and organization

1. Environments §2

   Formalize observations/actions and classify games by strategic properties.

2. Evaluation and analysis §§3–4

   Measure three distinct abilities, then vary modality, reasoning prompts, personas and human comparison.

Problem, claim and contribution

The benchmark's gap is interaction with other agents under visual and partial information, not ordinary single-agent task solving; the three measured abilities are named at the outset.

Abstract and Figure 2, PDF pp. 1–2 · Main paper · Additional source 2

Argument and section order

The environment taxonomy precedes the leaderboard, while perception, strategic prediction and interactive return receive separate evaluations.

Table 1, PDF p. 3; Tables 2–4, PDF pp. 4–6 · Main paper · Additional source 2

Figures, captions and visual explanation

The taxonomy table combines game properties with graded ability requirements. Page 6 contrasts multimodal/text-only bars with hatch patterns and averages, while below-random cells stay visible in the main table.

Table 1, PDF p. 3; Table 4 and Figure 3, PDF p. 6 · Main paper · Additional source 2

Tables, comparisons and evidence

Decision returns are normalized using random/oracle anchors; the main analysis adds human participants and failure cases rather than equating high perception with strategic competence.

Table 4, PDF p. 6; Figure 6 and §4.5, PDF p. 8 · Main paper · Additional source 2

Appendix and reproducibility

The supplement specifies exact model versions, per-game data/return rules, unnormalized returns, failure traces and extra environments, making the normalized main comparison auditable.

Supplement §§A–K, PDF pp. 1–24; Tables 5–11 · Main paper · Additional source 2

Clarity and writing conventions

The paper differentiates missing private-information reasoning from ignoring history, turning qualitative failures into task-specific explanations rather than generic model weakness.

§4.5, PDF p. 8; Supplement §H, PDF pp. 15–18 · Main paper · Additional source 2

What to reuse—and what not to infer

Transferable lesson: For an interactive benchmark, separate recognition, predicting others and acting, then expose random/oracle normalization and the information each player can observe.

Boundary: Normalized game return depends on reward and opponent protocol; personas in simulated games do not establish a model's stable real-world social disposition or ethics.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked

2026-09-26

Reading status

Writing-focused manuscript scan + selected visuals inspected

Main text

Manuscript-wide writing scan of PDF pp. 1–12: framing, argument sequence, section organization, figure/table captions, evaluation interpretation and limitations; reference sections identified. This is a writing-focused scan, not an exhaustive technical proof or reproduction audit. Main PDF pages 3 and 6 were rendered and visually inspected.

Appendix / supplement

Writing-focused scan of the separate supplementary PDF, pp. 1–24, including its organization, captions, protocol/evidence detail and limitation material where present; proofs and code listings were inspected for exposition, not independently verified or executed. Supplement §§A–K, PDF pp. 1–24; Tables 5–11. Linked video/audio demonstrations and non-PDF archive contents were not assessed.

Visually inspected PDF pages

3, 6

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.

• Official CVPR 2026 CVF open-access accepted manuscript; retrieved 2026-09-26 · 12 pages
• Official CVPR 2026 CVF supplementary PDF; retrieved 2026-09-26 · 24 pages