Writing study: SimScale: Learning to Drive via Real-World Simulation at Scale
← CVPR 2026 oral writing corpus
Haochen Tian, Tianyu Li, Haochen Liu, Jiazhi Yang, Yihang Qiu, Guang Li, junli wang, Yinfeng Gao, Zhang Zhang, Liang Wang, Hangjun Ye, Long Chen, Hongyang Li · Official CVPR 2026 oral record
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
- 10 physical pages
- Before references / appendix
- ≈ 8.16 page-equivalents
- Main figures / tables
- 5 / 4
- Attached appendix figures / tables
- 0 / 0
- Attached appendix span
- Separate file recorded below; not in this PDF total
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.
All detected figure and table locations
Main text
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 13 physical pages; 9 detected figures and 6 tables. These may include overlapping main-text material.
Located appendix only: starts on physical p.1; ≈ 12.94 page-equivalents, 9 figure labels and 6 table labels. This interval is distinct from the whole file.
| Detected heading | PDF page | Estimated span |
|---|---|---|
| Supplementary Material | 1 | ≈ 0.02 pp. |
| A. Related Work | 1 | ≈ 0.04 pp. |
| B. Extended Implementation Details | 1 | ≈ 0.03 pp. |
| C. Extended Experimental Results | 1 | ≈ 0.04 pp. |
| D. Additional Experimental Results | 1 | ≈ 0.04 pp. |
| E. Limitations and Broader Impact | 1 | ≈ 0.04 pp. |
| F. License of Assets | 1 | ≈ 8.77 pp. |
| References | 10 | ≈ 3.95 pp. |
Argument and organization
- 2. Methodology
Defines simulation, pseudo-expert trajectories, and co-training.
- 3. Experiments
Moves from fixed leaderboard protocols to scaling, intervention ablations, and scene examples.
Problem, claim and contribution
Missing rare driving states motivates expanding data coverage rather than claiming a new planner architecture.
§1; Figure 1 · Main paper · Additional source 2
Argument and section order
Pseudocode exposes perturbation, reactive rollout, sensor simulation, and filtering; recovery-based and planner-based experts are separately explained.
Algorithm 1 and §2.3 p. 4 · Main paper · Additional source 2
Figures, captions and visual explanation
Four matched scaling plots compare planners and supervision choices; scene strips pair trajectory maps with rendered camera views.
Figures 4–5 p. 7 · Main paper · Additional source 2
Tables, comparisons and evidence
Leaderboard captions distinguish privileged symbolic inputs, pseudo-expert supervision, and reward scoring; reactive/nonreactive tests probe the data-generation mechanism.
Tables 1–4 pp. 6,8 · Main paper · Additional source 2
Appendix and reproducibility
A table of contents maps extended experiments, limitations, and licenses; further tests vary real-data amount and rendering fidelity.
Supplement §§B–F · Main paper · Additional source 2
Clarity and writing conventions
The text calls the curves fitted log-quadratic trends and discusses plateaus/degradation, useful restraint around a scaling headline.
§3.3 p. 7 · Main paper · Additional source 2
What to reuse—and what not to infer
Transferable lesson: A data-scaling study should show how samples are produced, what supervision they contain, and where measured gains saturate.
Boundary: Fitted trends over examined scales are not universal scaling laws or a real-world safety guarantee.
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 main PDF pp. 1–8: framing, section structure, method exposition, figure/table captions, evaluation organization and conclusions; not an exhaustive technical proof audit or reproduction.
- Appendix / supplement
- Scanned the 13-page supplement's outline, implementation tables, full results, further scaling and fidelity experiments, qualitative sequences, limitations, and asset-license section.
- Visually inspected PDF pages
- 4, 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.