Writing study: Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments

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← ICLR 2026 oral writing corpus

Romain Froger, Pierre Andrews, Matteo Bettini, Amar Budhiraja, Ricardo Cabral, Virginie Do, Emilien Garreau, Jean-Baptiste Gaya, Hugo Laurençon, Maxime Lecanu, Kunal Malkan, Dheeraj Mekala, Pierre Ménard, Gerard Bertran, Ulyana Piterbarg, Mikhail Plekhanov, Mathieu Rita, Andrey Rusakov, Vladislav Vorotilov, Mengjuew Wang, Ian Yu, Amine Benhalloum, Grégoire Mialon, Thomas Scialom · Official ICLR 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: Datasets, benchmarks & measurement resources (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

32 physical pages

Before references / appendix

≈ 10.26 page-equivalents

Main figures / tables

10 / 3

Attached appendix figures / tables

10 / 4

Attached appendix span

≈ 17.89 page-equivalents

Before references / appendix: ≈ 32.06%References / intervening material: ≈ 12.03%Attached appendix: ≈ 55.91%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	2	≈ 0.65 pp.	2.03%
2 RELATED WORK	2	≈ 0.88 pp.	2.75%
3 ARE: SCALING UP AGENT ENVIRONMENTS AND EVALUATIONS	3	≈ 1.17 pp.	3.66%
4 GAIA2: EXPANDING GENERAL AGENT EVALUATION	4	≈ 1.64 pp.	5.13%
5 EXPERIMENTS	6	≈ 4.15 pp.	12.97%
6 CONCLUSION & DISCUSSION	10	≈ 0.51 pp.	1.59%
ACKNOWLEDGEMENTS	11	≈ 0.15 pp.	0.47%
REFERENCES	11	≈ 3.85 pp.	12.03%
A ARE APPENDIX	15	≈ 8 pp.	25%
B GAIA2 APPENDIX	23	≈ 9.89 pp.	30.91%

All detected figure and table locations

Main text

• Figure 1 · p. 1
• Figure 2 · p. 3
• Figure 3 · p. 3
• Figure 4 · p. 5
• Table 1 · p. 6
• Table 2 · p. 7
• Figure 5 · p. 7
• Figure 6 · p. 8
• Figure 7 · p. 8
• Figure 8 · p. 9
• Figure 9 · p. 9
• Figure 10 · p. 10
• Table 3 · p. 10

Attached appendix

• Figure 2 · p. 16
• Figure 11 · p. 17
• Table 4 · p. 18
• Figure 12 · p. 18
• Figure 13 · p. 19
• Figure 14 · p. 21
• Figure 15 · p. 27
• Figure 16 · p. 28
• Figure 17 · p. 29
• Table 5 · p. 29
• Figure 18 · p. 30
• Table 6 · p. 31
• Figure 19 · p. 32
• Table 7 · p. 32

Argument and organization

1. Reusable platform, benchmark, verifier

   Separates infrastructure abstractions from the concrete Mobile scenarios and their success definition.

2. Capability and resource-sensitive evaluation

   Adds time-mode, collaboration, and cost analyses to overall benchmark scores.

Problem, claim and contribution

The motivating gap is environmental change independent of agent action, not simply another harder task collection. Contributions distinguish the ARE platform, Gaia2 scenarios, and empirical study.

Introduction, p. 2 · Main paper

Argument and section order

Core capabilities are separated from Noise and Agent2Agent augmentations. The 800 unique scenarios plus 320 derived scenarios are stated explicitly, avoiding an inflated interpretation of 1,120 independently authored tasks.

Sections 4–4.1, pp. 4–5 · Main paper

Figures, captions and visual explanation

The framework diagram places agent and user outside the environment boundary and shows notification policy, queue, loop, and log separately. This makes asynchronous behavior a visible design property.

Figure 2, p. 3 · Main paper

Tables, comparisons and evidence

Default-versus-instant time bars isolate generation latency as an evaluation factor. Adjacent collaboration curves show benefits are model-dependent rather than presenting multi-agent decomposition as uniformly helpful.

Figures 8 and 10, pp. 9–10 · Main paper

Appendix and reproducibility

Verifier validation includes human labels, alternate judging models, an observed reward-hacking failure, and exact timing tolerances. Annotation-interface non-release and model-specific inference exceptions are disclosed.

Appendices A.4.4, B.1.3, B.2.3–B.4, pp. 22–31 · Main paper

Clarity and writing conventions

Table 3 explicitly labels main-agent columns and app-agent rows, but the surrounding prose swaps the 16.2 and 18.3 cross-model pairings. Role-sensitive tables need a final prose-to-cell consistency check.

Section 5.3 and Table 3, pp. 9–10 · Main paper

What to reuse—and what not to infer

Transferable lesson: For systems benchmarks, define the environment clock, observability, verifier, and resource accounting as parts of the experiment—not implementation trivia.

Boundary: Success enforces oracle write-tool counts and dependencies, rejecting some equivalent outcomes or corrected mistakes. The verifier includes an LLM and is not a formal guarantee. Costs are historical, and limited parallel-tool ablations do not prove scaffold independence for every model.

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 1–6

Appendix / supplement

Pages 15–32, appendices A–B: platform, annotation, verifier, orchestration, implementation exceptions, and extra experiments

Visually inspected PDF pages

3, 9, 10

• ICLR 2026 final proceedings · 32 pages