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Writing study: LLMs Get Lost In Multi-Turn Conversation

← ICLR 2026 oral writing corpus

Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, Jennifer Neville · Official ICLR 2026 oral record

Figure, table and section ledger

Editorial contribution type: Empirical analysis, diagnosis & auditing (primary) · Datasets, benchmarks & measurement resources.

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
41 physical pages
Before references / appendix
≈ 10.74 page-equivalents
Main figures / tables
5 / 1
Attached appendix figures / tables
5 / 9
Attached appendix span
≈ 24.89 page-equivalents
Before references / appendix: ≈ 26.2%References / intervening material: ≈ 13.1%Attached appendix: ≈ 60.71%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≈ 0.86 pp.2.1%
2 BACKGROUND AND RELATED WORK2≈ 0.79 pp.1.93%
3 SIMULATING UNDERSPECIFIED, MULTI-TURN CONVERSATION3≈ 1.38 pp.3.37%
4 EXPERIMENT4≈ 3 pp.7.32%
5 RESULTS7≈ 1.79 pp.4.37%
6 IMPLICATIONS SUMMARY9≈ 0.82 pp.2%
7 CONCLUSION10≈ 0.17 pp.0.41%
8 ETHICS STATEMENT10≈ 0.95 pp.2.32%
9 REPRODUCIBILITY STATEMENT11≈ 0.24 pp.0.59%
REFERENCES11≈ 5.37 pp.13.1%
A RELATED WORK ON UNDERSPECIFICATION17≈ 0.51 pp.1.24%
B PRECISE DEFINITION OF SHARDED INSTRUCTIONS17≈ 1.05 pp.2.56%
C SEMI-AUTOMATIC SHARDING PROCESS18≈ 1.03 pp.2.51%
D INSPECTION OF SIMULATED SHARDED CONVERSATION19≈ 0.99 pp.2.41%
E CONCRETE EXAMPLE OF LOSS IN APTITUDE VS. RELIABILITY20≈ 1.18 pp.2.88%
F QUALITATIVE ANALYSES OF SIMULATION LOGS21≈ 3.76 pp.9.17%
G IMPLICATIONS25≈ 3.99 pp.9.73%
H ASSISTANT RESPONSE CATEGORIZATION29≈ 0.18 pp.0.44%
I MODEL ACCESS29≈ 0.68 pp.1.66%
J TASK-SPECIFIC IMPLEMENTATION DETAILS30≈ 3.17 pp.7.73%
K EXAMPLE SIMULATED CONVERSATION33≈ 0.21 pp.0.51%
L GRADUAL SHARDING IMPLEMENTATION33≈ 0.82 pp.2%
M TEMPERATURE EXPERIMENT IMPLEMENTATION34≈ 0.46 pp.1.12%
N RECAP & SNOWBALL EXPERIMENT IMPLEMENTATION35≈ 0.34 pp.0.83%
O ON OBTAINING DETERMINISTIC OUTPUTS FROM LLMS35≈ 6.51 pp.15.88%
All detected figure and table locations

Argument and organization

  1. Problem and controlled conversation simulator

    Contrasts episodic evaluation with gradually disclosed requirements.

  2. Metrics, findings and causal hypotheses

    Separates mean performance, high-percentile aptitude and interpercentile unreliability.

  3. Implications by audience and appendices

    Routes findings to builders, practitioners and users; preserves protocols and full prompts.

Problem, claim and contribution

The paper names a recognizable failure mode, then operationalizes it with sharding instead of relying on anecdotes about chat quality.

Sections 1–3 · Main paper

Argument and section order

FULL, CONCAT, SHARDED, RECAP and SNOWBALL form interpretable controls; CONCAT specifically tests whether rephrasing rather than conversational disclosure causes degradation.

Section 3.3, Figure 3 · Main paper

Figures, captions and visual explanation

The simulator diagram highlights the evaluated assistant separately from judge components and distinguishes failed, non-answer and successful paths.

Figure 2, p. 3 · Main paper

Tables, comparisons and evidence

Table 1 uses repeated task columns and degradation shading, while Figure 5 first teaches the percentile encoding before applying it. The combined page is dense and icon-only headers need the caption.

Table 1 and Figure 5, p. 7 · Main paper

Appendix and reproducibility

The appendix includes a counterexample task (translation), annotation taxonomy, dated model versions, complete prompts and a failed conversation transcript—not only extra positive results.

Appendices G.3, H–K and prompts, pp. 28–41 · Main paper

Clarity and writing conventions

Bold result sentences aid scanning, but categorical statements about any multi-turn conversation are stronger than the controlled English analytical-task sample; later limitations restore the narrower scope.

Section 5.3 versus Section 8 · Main paper

What to reuse—and what not to infer

Transferable lesson: Design a control that isolates the proposed failure mechanism, then teach any new metric visually before presenting its cross-model distribution.

Boundary: Treat verbosity and premature-answer analyses as observational, not causal interventions. The 39% headline is an aggregated relative drop, not 39 percentage points. Appendix D alternates 200 and 100 inspected conversations; Appendix L alternates eight and 31 selected instructions, so audit counts before reuse.

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 1–11, Sections 1–9
Appendix / supplement
Pages 17–41, Appendices A–O and all sharding/simulation prompts
Visually inspected PDF pages
3, 7