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
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 | ≈ 0.86 pp. | 2.1% |
| 2 BACKGROUND AND RELATED WORK | 2 | ≈ 0.79 pp. | 1.93% |
| 3 SIMULATING UNDERSPECIFIED, MULTI-TURN CONVERSATION | 3 | ≈ 1.38 pp. | 3.37% |
| 4 EXPERIMENT | 4 | ≈ 3 pp. | 7.32% |
| 5 RESULTS | 7 | ≈ 1.79 pp. | 4.37% |
| 6 IMPLICATIONS SUMMARY | 9 | ≈ 0.82 pp. | 2% |
| 7 CONCLUSION | 10 | ≈ 0.17 pp. | 0.41% |
| 8 ETHICS STATEMENT | 10 | ≈ 0.95 pp. | 2.32% |
| 9 REPRODUCIBILITY STATEMENT | 11 | ≈ 0.24 pp. | 0.59% |
| REFERENCES | 11 | ≈ 5.37 pp. | 13.1% |
| A RELATED WORK ON UNDERSPECIFICATION | 17 | ≈ 0.51 pp. | 1.24% |
| B PRECISE DEFINITION OF SHARDED INSTRUCTIONS | 17 | ≈ 1.05 pp. | 2.56% |
| C SEMI-AUTOMATIC SHARDING PROCESS | 18 | ≈ 1.03 pp. | 2.51% |
| D INSPECTION OF SIMULATED SHARDED CONVERSATION | 19 | ≈ 0.99 pp. | 2.41% |
| E CONCRETE EXAMPLE OF LOSS IN APTITUDE VS. RELIABILITY | 20 | ≈ 1.18 pp. | 2.88% |
| F QUALITATIVE ANALYSES OF SIMULATION LOGS | 21 | ≈ 3.76 pp. | 9.17% |
| G IMPLICATIONS | 25 | ≈ 3.99 pp. | 9.73% |
| H ASSISTANT RESPONSE CATEGORIZATION | 29 | ≈ 0.18 pp. | 0.44% |
| I MODEL ACCESS | 29 | ≈ 0.68 pp. | 1.66% |
| J TASK-SPECIFIC IMPLEMENTATION DETAILS | 30 | ≈ 3.17 pp. | 7.73% |
| K EXAMPLE SIMULATED CONVERSATION | 33 | ≈ 0.21 pp. | 0.51% |
| L GRADUAL SHARDING IMPLEMENTATION | 33 | ≈ 0.82 pp. | 2% |
| M TEMPERATURE EXPERIMENT IMPLEMENTATION | 34 | ≈ 0.46 pp. | 1.12% |
| N RECAP & SNOWBALL EXPERIMENT IMPLEMENTATION | 35 | ≈ 0.34 pp. | 0.83% |
| O ON OBTAINING DETERMINISTIC OUTPUTS FROM LLMS | 35 | ≈ 6.51 pp. | 15.88% |
All detected figure and table locations
Argument and organization
- Problem and controlled conversation simulator
Contrasts episodic evaluation with gradually disclosed requirements.
- Metrics, findings and causal hypotheses
Separates mean performance, high-percentile aptitude and interpercentile unreliability.
- 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
- ICLR 2026 final proceedings · 41 pages