Writing study: Focus and Dilution: The Multi-stage Learning Process of Attention

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← ICML 2026 oral writing corpus

Zheng-An Chen, Pengxiao Lin, Zhi-Qin John Xu, Tao Luo · Official ICML 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: Theory & formal analysis (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

54 physical pages

Before references / appendix

≈ 9.26 page-equivalents

Main figures / tables

3 / 0

Attached appendix figures / tables

2 / 0

Attached appendix span

≈ 41.91 page-equivalents

Before references / appendix: ≈ 17.15%References / intervening material: ≈ 5.24%Attached appendix: ≈ 77.61%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	≈ 1.04 pp.	1.93%
2. Related Works	2	≈ 0.82 pp.	1.52%
3. Preliminaries	3	≈ 1.13 pp.	2.09%
4. Theoretical results	4	≈ 2.98 pp.	5.52%
5. Empirical evidence	7	≈ 2.54 pp.	4.7%
6. Conclusion and Limitations	9	≈ 0.19 pp.	0.35%
Impact Statement	10	≈ 0.08 pp.	0.15%
Acknowledgements	10	≈ 0.14 pp.	0.26%
References	10	≈ 2.82 pp.	5.22%
A. Theoretical details in Sec. 3	13	≈ 3.1 pp.	5.74%
B. Theoretical details in Sec. 4	16	≈ 16.2 pp.	30%
C. Theoretical details in Sec. 4.4	32	≈ 21.09 pp.	39.06%
D. Detailed Experiment Setup	53	≈ 1.52 pp.	2.81%

All detected figure and table locations

Main text

• Figure 1 · p. 3
• Figure 2 · p. 8
• Figure 3 · p. 9

Attached appendix

• Figure 4 · p. 54
• Figure 5 · p. 54

Argument and organization

1. 1 Introduction; 2 Related Work; 3 Preliminaries

   Introduces a stagewise attention-learning question and a tractable Markov-data model.

2. 4 Theoretical Results

   Connects condensation, focus, dilution and asymmetric emergence through successive local analyses.

3. 5 Empirical Evidence; 6 Conclusion and Limitations

   Tests stage signatures with synthetic and text data, then separates proven phases from later-cycle hypotheses.

Problem, claim and contribution

The target is the changing role of attention during learning, with multiple internal diagnostics replacing loss alone as the explanatory object.

Introduction, p.1; Section 4, pp.3-7 · Main paper

Argument and section order

The named phases provide a narrative spine, but their statements retain initialization, trajectory-neighborhood and small-asymmetry conditions.

Sections 4.1-4.4, pp.3-7 · Main paper

Figures, captions and visual explanation

Stage colors align loss traces, cosine heatmaps, PCA snapshots, attention maps and norm diagnostics; the next page reuses the diagnostic vocabulary for text data.

Figure 2, p.8; Figure 3, p.9 · Main paper

Tables, comparisons and evidence

The empirical text-data runs use the simplified architecture, while multi-layer, multi-head and residual variants provide additional observations rather than extending the theorem to production language models.

Section 5, pp.8-9 · Main paper

Appendix and reproducibility

The proof blocks mirror the stagewise organization, and experimental details identify Adam training, sequence length and visualization transformations separately from the population gradient-flow theory.

Appendices A-B, pp.13,20,28; Appendix D, p.53 · Main paper

Clarity and writing conventions

The paper marks subsequent cycles as a hypothesis and explicitly leaves layer normalization and layer interactions outside the established account.

Later-stage discussion, p.8; limitations, p.9 · Main paper

What to reuse—and what not to infer

Transferable lesson: Give a dynamical theory a consistent stage vocabulary across statements and figures, while marking where a proved local transition becomes an empirical or speculative continuation.

Boundary: The guarantees concern a simplified attention model, Markov data, small initialization and stated trajectory conditions; Adam experiments and text-corpus signatures do not establish a universal training law for large language models.

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, 20, 28, 53. Remaining appendix proofs and details were not exhaustively read. No separately linked supplement inspected.

Visually inspected PDF pages

8, 9

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.

• Published proceedings PDF, PMLR volume 306, retrieved 2026-10-07 · 54 pages