Writing study: CoEvol-NO: State and Coordinate Co-Evolution with an Error-Driven Predictor-Corrector Paradigm for Neural Operator Transformer
← ICML 2026 oral writing corpus
Jianqiao Zeng, Ruocheng Wang, Yanzhi Liu, Hao Xiong, Junchi Yan · Official ICML 2026 oral record
Figure, table and section ledger
Editorial contribution type: Architecture & representation (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
- 27 physical pages
- Before references / appendix
- ≈ 9.15 page-equivalents
- Main figures / tables
- 3 / 10
- Attached appendix figures / tables
- 5 / 9
- Attached appendix span
- ≈ 14.86 page-equivalents
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 | ≈ 0.98 pp. | 3.63% |
| 2. Related Work | 2 | ≈ 0.94 pp. | 3.48% |
| 3. Preliminary | 3 | ≈ 0.49 pp. | 1.81% |
| 4. Methodology | 4 | ≈ 1.66 pp. | 6.15% |
| 5. Experiment | 5 | ≈ 3.9 pp. | 14.44% |
| 6. Conclusion and Limitation | 9 | ≈ 0.32 pp. | 1.19% |
| Impact Statement | 10 | ≈ 0.05 pp. | 0.19% |
| Acknowledgments | 10 | ≈ 0.05 pp. | 0.19% |
| References | 10 | ≈ 2.99 pp. | 11.07% |
| A. Theoretical Analysis and Derivations | 13 | ≈ 2.37 pp. | 8.78% |
| B. Theoretical Motivation for the Prediction Target Selection | 15 | ≈ 0.84 pp. | 3.11% |
| C. CoEvol-NO Algorithm | 16 | ≈ 0.41 pp. | 1.52% |
| D. Stability and Conditioning Analysis of Update Mechanisms | 16 | ≈ 1.33 pp. | 4.93% |
| E. Full Gradient Ablation: 8-Combination Study | 18 | ≈ 0.38 pp. | 1.41% |
| F. Full Momentum Ablation | 18 | ≈ 0.62 pp. | 2.3% |
| G. Comparison with Attention Residuals (AttnRes) | 19 | ≈ 0.33 pp. | 1.22% |
| H. Extended Scaling Analysis | 19 | ≈ 2.13 pp. | 7.89% |
| I. Statistical Significance and Stability | 21 | ≈ 0.18 pp. | 0.67% |
| J. In-depth Visualization of Latent Dynamics | 21 | ≈ 3.65 pp. | 13.52% |
| K. Experimental Details | 25 | ≈ 1.36 pp. | 5.04% |
| L. Efficiency Analysis | 26 | ≈ 0.42 pp. | 1.56% |
| M. Runtime and Memory Benchmarks | 27 | ≈ 0.83 pp. | 3.07% |
All detected figure and table locations
Main text
Argument and organization
- 1 Introduction; 2 Related Work; 3 Preliminaries
Frames competing mesh/state interaction designs before the predictor-corrector analogy.
- 4 Methodology
Separates exact latent-state correction, approximate mesh updates and optimizer enhancements.
- 5 Experiments; 6 Conclusion and Limitation
Tests benchmark quality, component choices, resolution transfer, shifts and cross-architecture applicability.
Problem, claim and contribution
The architecture is motivated by a proposed geometry-versus-memory trade-off, but layer-wise latent evolution should not be confused with directly verified physical-time dynamics.
Abstract, p.1; Section 4.2, p.4 · Main paper
Argument and section order
Prediction and correction receive separate definitions, and the ideal representation is explicitly replaced by a learned target rather than intermediate ground truth.
Remark 3.1 and Section 4.2, p.4 · Main paper
Figures, captions and visual explanation
The ablation table separates exact and approximate updates and labels loss variants; adjacent transfer tables make resolution and physical-condition shifts distinct evaluation axes.
Tables 5-7, p.8 · Main paper
Tables, comparisons and evidence
The result captions identify copied versus reimplemented baselines, while the OOD table retains worse field/coefficient errors despite improved rank correlation.
Table 2, p.6; Table 7 and discussion, p.8 · Main paper
Appendix and reproducibility
The gradient derivation supports the stated mesh-size complexity, and the runtime supplement reports an approximately 1.7-fold constant overhead despite linear scaling.
Appendix A.1, p.13; Appendix L, p.26 · Main paper
Clarity and writing conventions
The limitation paragraph admits that exact correction on every module can hurt and that conditioning and deep-network behavior remain unresolved.
Conclusion and Limitation, p.9 · Main paper
What to reuse—and what not to infer
Transferable lesson: Separate asymptotic scaling from measured constant cost, and report accuracy, ranking and distribution-shift results without merging their different conclusions.
Boundary: Linear complexity holds with latent size and feature width controlled; PCA trajectories and improved PDE errors do not prove recovery of physical laws or universal stability.
Apply this lesson using the argument and evidence worksheet.
Inspection record and sources
- Checked
- 2026-10-07
- Reading status
- Writing-focused manuscript scan + selected visuals inspected
- Main text
- Writing-oriented scan of the main argument through physical p.9, with focused physical-page text inspection on 1, 3, 4, 5, 6, 7, 8, 9. Framing, section progression, mechanism/proof explanation, displays, comparison conditions and conclusions were inspected. This is not exhaustive technical reading, proof verification or reproduction.
- Appendix / supplement
- Appendix organization and main-text pointers were checked; focused text inspection of physical pages 13, 26. Remaining appendix proofs and details were not exhaustively read. No separately linked supplement inspected.
- Visually inspected PDF pages
- 4, 8
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.