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These results embed part geometry, manual pages and reference images from PartNet (via Manual-PA), IKEA-Manual, AssemblyBench (Fusion 360 Gallery) and Fantastic Breaks inside the recorded episodes and transcripts. These assets keep their original rights. Access is granted for non-commercial research only, and you must comply with the terms of every source dataset.
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AssemblyWorldBench Results
Complete records of every agent run behind the main result tables of AssemblyWorld:
Rethinking 3D Assembly with General-Purpose Agents: for each evaluated sample, the prompt,
the full agent transcript with timestamped tool calls, the agent's own report, the exported
final episode, and its geometric scores, plus the aggregates the paper reports. The benchmark
itself is AssemblyWorld/AssemblyWorldBench.
index/samples.parquet has one row per sample (4,624 rows): table, system, block, sample,
run status, the agent's self-reported outcome, SCD / PA / SR, wall time, tokens, cost and
WebMCP call count, with the path to the sample directory. It is what the dataset viewer shows.
Contents
| Directory | Paper | Agent system | Samples |
|---|---|---|---|
assemblyworldbench/<system>/ |
Table 1, AssemblyWorldBench | 8 systems: Claude Fable 5.1, Claude Opus 5, Claude Sonnet 5 (Claude Code); GPT-6 Astra, GPT-5.6 Sol, GPT-5.6 Terra, DeepSeek V4.1 Flash, Qwen3.8 Max (Codex) | 100 each |
partnet/gpt-6-astra/ |
Table 2, PartNet-Assembly | GPT-6 Astra + Codex | storage 148 × 3 references; chair 791 and table 533 without reference and with a final image; chair and table 100-object manual subsamples |
ikea-manual/gpt-6-astra/ |
Table 3, IKEA-Manual | GPT-6 Astra + Codex | 102 |
assemblybench/gpt-6-astra/ |
Table 4, AssemblyBench | GPT-6 Astra + Codex | 280 (279 reported) |
fantastic-breaks/gpt-6-astra/ |
Table 5, Fantastic Breaks | GPT-6 Astra + Codex | 150 |
Every directory follows <table>/<system>/<block>/ with run.json, task.txt,
samples/<sample>/ (input.json, prompt.txt, result.json, conversation.jsonl,
final.episode.zip) and evaluation/ (metrics.jsonl, metrics_summary.json, meta.json).
Each system has an experiment.json naming the paper table and row. AGENTS.md documents
every file and field, the per-harness usage conventions, and all edits made at export.
Supplementary studies in the paper (robustness to layout, distractor and missing-part perturbations; GARF refinement) are not included.
Reproducing the scores
Every block directory is a valid run directory for
assembly-world-agent:
# one block
uv run --locked --extra episodes python scripts/evaluate_run.py \
results/ikea-manual/gpt-6-astra/ikea-manualbook --output /tmp/ikea
# one Table 1 system, aggregated with the frozen benchmark rules
uv run --locked --extra episodes python scripts/evaluate_run.py \
results/assemblyworldbench/claude-fable-5-1/{partnet-none,partnet-final-image,ikea-manualbook,assemblybench-manualbook,fantastic-breaks-none} \
--benchmark results/assemblyworldbench/benchmark/benchmark.json --output /tmp/fable
The evaluator rebuilds the ground truth from the pinned source dataset revisions on
Hugging Face. Scores use assembly-evaluation-v2: SCD (whole-shape Chamfer ×1000), PA
(fraction of parts within Chamfer 0.01 of their matched part) and SR (all parts correct).
Re-scoring reproduces the recorded metrics.jsonl rows.
Known limitations
- AssemblyBench: the reported aggregate excludes sample 6772 (the model refused the task) and uses the selected retry of sample 6994. The original 280-sample aggregate used the first attempt of 6994, which is not included, so only the 279-sample number is reproducible.
- The four collaborator-run PartNet blocks (chair and table without reference and with a final image) keep only the attempt selected for each sample; their superseded attempts were not transferred, so retry counts are unknown.
- A few runs ended with a CLI error after the episode was exported (
result.json.status = failed,archive.status = saved); they are scored like any other sample. - Model reasoning text is not exported by the agent CLIs; only reasoning token counts appear.
Terms
The final episodes embed source part geometry, and transcripts embed the reference images
given to the agent. These assets keep their original rights; see LICENSE.md. Source
datasets: AssemblyWorld/partnet-manualpa,
AssemblyWorld/ikea-manual,
AssemblyWorld/assemblybench,
AssemblyWorld/fantastic-breaks.
Please also cite Mo et al., PartNet, 2019; Zhang et al., Manual-PA, 2025;
Wang et al., IKEA-Manual, 2022; Li et al., AssemblyBench, 2026; Lamb et al.,
Fantastic Breaks, 2023.
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