Writing study: MrRoPE: Mixed-radix Rotary Position Embedding
← ICLR 2026 oral writing corpus
Qingyuan Tian, Wenhong Zhu, Xiaoran Liu, Xiaofeng Wang, Rui Wang · Official ICLR 2026 oral record
Figure, table and section ledger
Editorial contribution type: Architecture & representation design (primary) · Empirical analysis, diagnosis & auditing.
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
- 16 physical pages
- Before references / appendix
- ≈ 9.44 page-equivalents
- Main figures / tables
- 6 / 3
- Attached appendix figures / tables
- 2 / 2
- Attached appendix span
- ≈ 4.56 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 | ≈ 1.08 pp. | 6.75% |
| 2 ROPE AND RADIX THEORY | 2 | ≈ 1.5 pp. | 9.38% |
| 3 MRROPE: A UNIFY FRAMEWORK FOR ROPE EXTENSION | 4 | ≈ 2.44 pp. | 15.25% |
| 4 EXPERIMENTS | 6 | ≈ 3.31 pp. | 20.69% |
| 5 CONCLUSION | 9 | ≈ 0.34 pp. | 2.13% |
| ETHICS STATEMENT | 10 | ≈ 0.12 pp. | 0.75% |
| REPRODUCIBILITY STATEMENT | 10 | ≈ 0.12 pp. | 0.75% |
| REFERENCES | 10 | ≈ 2 pp. | 12.5% |
| A RELATED WORKS | 12 | ≈ 1.73 pp. | 10.81% |
| B DETAILS OF MRROPE METHODOLOGY | 14 | ≈ 1.25 pp. | 7.81% |
| C ADDITIONAL EXPERIMENTS RESULTS | 15 | ≈ 0.37 pp. | 2.31% |
| D USE OF LLMS | 15 | ≈ 0.63 pp. | 3.94% |
| E LIMITATION | 16 | ≈ 0.57 pp. | 3.56% |
All detected figure and table locations
Main text
Attached appendix
Argument and organization
- Introduction and mixed-radix interpretation
Recast competing frequency-scaling schemes as choices within one parameterization.
- Uniform and progressive MrRoPE
Present two small interventions before examining language modeling, retrieval and downstream tasks.
- Analysis and supplementary experiments
Connect empirical context extension to a cosine-sum proxy and expose implementation choices.
Problem, claim and contribution
The contribution is introduced as a common language for existing context-extension methods, making the subsequent uniform/progressive choices interpretable as parameter changes rather than an unrelated architecture.
Sections 1–3, pages 1–6 · Main paper
Argument and section order
The method separates boundary selection, middle-band scaling and attention rescaling. This decomposition helps distinguish the actual new parameterization from retained YaRN implementation components.
Section 3; Appendix B, pages 14–15 · Main paper
Figures, captions and visual explanation
Figure 1 uses aligned frequency bands and radix blocks to translate a numerical encoding into a visual correspondence. Figure 3 then plots cumulative scaling factors, complementing rather than duplicating the symbolic explanation.
Figure 1, page 2; Section 3 and Figure 3 · Main paper
Tables, comparisons and evidence
The evidence moves from perplexity to length-by-depth retrieval heatmaps and then RULER and downstream benchmarks. These answer different questions and should not be collapsed into a single effective-context claim.
Section 4, Tables 1–3, pages 7–9 · Main paper
Appendix and reproducibility
Derivations, hyperparameters and additional model results are separated into named appendices. However, inconsistent model labels and alpha/beta conventions require readers to reconcile the implementation description rather than infer settings from one caption.
Appendices A–C, pages 12–16 · Main paper
Clarity and writing conventions
Some broad superiority wording is stronger than the displayed comparisons: progressive scaling is not the lowest-perplexity choice at every length, including Qwen at 32K. Explicit exceptions would strengthen the argument.
Table 1, page 7; Section 4 discussion · Main paper
What to reuse—and what not to infer
Transferable lesson: Use a shared mathematical parameterization and a matching visual vocabulary to explain a small method change; evaluate distinct consequences with distinct diagnostics instead of treating one metric as a universal proxy.
Boundary: The cosine-sum analysis is a proxy under assumptions, not a guarantee of usable context length. Preserve per-model and per-length exceptions, and resolve appendix notation/model-label inconsistencies before reproducing the method.
Apply this lesson using the argument and evidence worksheet.
Inspection record and sources
- Checked
- 2026-09-19
- Reading status
- Full text + selected visuals inspected
- Main text
- Pages 1–10, Sections 1–5, ethics and reproducibility statements
- Appendix / supplement
- Pages 12–16, Appendices A–E: interpolation derivations, implementation, extra evaluation and limitations
- Visually inspected PDF pages
- 2, 7, 8
- ICLR 2026 final proceedings · 16 pages