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Writing study: Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models

← ICML 2026 oral writing corpus

Songwei Liu, Chao Zeng, Chenqian Yan, Xurui Peng, Xing Wang, Fangmin Chen, Xing Mei · Official ICML 2026 oral record

Figure, table and section ledger

Editorial contribution type: Training, objectives & optimization (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
18 physical pages
Before references / appendix
≈ 8.1 page-equivalents
Main figures / tables
2 / 3
Attached appendix figures / tables
2 / 7
Attached appendix span
≈ 7.91 page-equivalents
Before references / appendix: ≈ 45%References / intervening material: ≈ 11.06%Attached appendix: ≈ 43.94%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 headingStarts on PDF pageEstimated spanShare of entire PDF
1. Introduction1≈ 1.25 pp.6.94%
2. Related Work2≈ 1.24 pp.6.89%
3. Method3≈ 2.76 pp.15.33%
4. Experiments6≈ 2.24 pp.12.44%
5. Conclusion8≈ 0.21 pp.1.17%
Impact Statement9≈ 0.05 pp.0.28%
References9≈ 1.99 pp.11.06%
A. Explanation of Approximation 111≈ 0.6 pp.3.33%
B. Derivation of Error Accumulation Steps11≈ 1.67 pp.9.28%
C. Empirical Study of Error Accumulation Steps13≈ 0.46 pp.2.56%
D. Compatibility with Different Solvers.13≈ 0.96 pp.5.33%
E. Timestep-Aware Quantization Error14≈ 0.98 pp.5.44%
F. Ablation experiment of regularization term λ115≈ 0.45 pp.2.5%
G. The impact of inference steps on TCEC performance16≈ 0.42 pp.2.33%
H. Inference Overhead of TCEC16≈ 0.15 pp.0.83%
I. Calibration Dataset Ablation16≈ 0.7 pp.3.89%
J. Additional comparison with QNCD17≈ 0.61 pp.3.39%
K. Visual Quality Results.18≈ 0.51 pp.2.83%
L. Human Evaluation18≈ 0.4 pp.2.22%
All detected figure and table locations

Argument and organization

  1. 1 Introduction; 2 Related Work

    Moves from diffusion deployment cost to the distinction between per-step quantization error and its accumulation.

  2. 3 Method

    Derives propagation, introduces computational approximations and then constructs timestep-aware compensation.

  3. 4 Experiments; 5 Conclusion; Appendix A-L

    Separates implementation and image/video comparisons from overhead, with derivations, sensitivity and human evaluation navigated in the appendix.

Problem, claim and contribution

The abstract connects an error-propagation explanation to a correction overlay and states both a fidelity gain and its additional latency.

Abstract and Section 1, p.1 · Main paper

Argument and section order

The method roadmap names two obstacles to using the derivation directly, and later subsections answer computational complexity and estimating per-step error in that order.

Section 3 opening, p.3; Sections 3.2-3.3, p.5 · Main paper

Figures, captions and visual explanation

The overview aligns full-precision, quantized and corrected denoising paths with a separate trajectory schematic; arrows and labels redundantly explain the gray/red/green encoding.

Figure 1, p.3 · Main paper

Tables, comparisons and evidence

The main image table separates quality from similarity and groups model, bit width and compensation overlay, while the following overhead table compares the same engine with and without correction.

Table 1, p.7; Table 3 and Hardware Resource Savings, p.8 · Main paper

Appendix and reproducibility

Appendix G gives the lower-step regime where gains weaken; H explains overhead and I investigates calibration size. These qualify the broad main conclusion rather than merely add examples.

Appendices G-I, p.16 · Main paper

Clarity and writing conventions

Approximations are explicitly labelled before the simplified correction, but the conclusion uses broad superiority language that must still be read with the model/metric conditions in the tables.

Section 3.2, p.5; Section 5, p.8 · Main paper

What to reuse—and what not to infer

Transferable lesson: Present a theoretical derivation, the approximations needed to implement it, and the measured cost of the resulting correction as distinct stages.

Boundary: No independent proof validation was performed; favorable fidelity does not mean every quality metric or low-step setting improves.

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.8, with focused physical-page text inspection on 1, 3, 5, 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 12, 16. Remaining appendix proofs and details were not exhaustively read. No separately linked supplement inspected.
Visually inspected PDF pages
3, 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.