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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
json dict | __key__ string | __url__ string |
|---|---|---|
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00028 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00029 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00078 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00079 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00080 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00081 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00082 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00083 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00085 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00086 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00087 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00088 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00089 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00090 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00091 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00092 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00093 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00094 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00095 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00096 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00097 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00098 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
{
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} | table1/maze2d/ordinary_easy/k10_cot/_rank_summaries/rank_00099 | hf://datasets/novastar111/uwm_paper_eval_trajectories@2655748cc8768a33933f886ea87238f2ffacd98d/table1/maze2d/ordinary_easy/k10_cot.tar.gz |
End of preview.
UWM paper evaluation trajectories
Complete, unselected model outputs for the UWM paper tables. 230/230 planned run archives are currently published; remaining rows are evaluations still running or not yet complete.
Each archive contains all available per-episode generated observations (gen_obs/), environment renders (renders/), rollout GIFs, verbatim generated reasoning text, actions, episode statistics, and the run summary. Text/JSON metadata is scrubbed of machine-local paths before publication.
Agent-generated observation images are required and included for CoT, forward-thinking, and branching runs. The NonCoT action-chunk policy emits no imagined image in the evaluated protocol (n_imagined=0); for those rows this field is not applicable, and the archive contains the actual actions, environment frames, GIF, and stats.
Table1
| Task | Eval set | Model | Trajectory archive | Checkpoint | Eval data | Result |
|---|---|---|---|---|---|---|
| sokoban | Ordinary Hard | k1_noncot |
download | model | dataset | 47.0% |
| sokoban | Ordinary Hard | k3_cot |
download | model | dataset | 53.0% |
| sokoban | Ordinary Hard | k3_noncot |
download | model | dataset | 10.0% |
| sokoban | Ordinary Hard | k5_cot |
download | model | dataset | 40.0% |
| sokoban | Ordinary Hard | k5_noncot |
download | model | dataset | 2.0% |
| sokoban | Ordinary Hard | k10_cot |
download | model | dataset | 15.0% |
| sokoban | Ordinary Hard | k10_noncot |
download | model | dataset | 0.0% |
| sokoban | Ordinary Hard | kinf_cot |
download | model | dataset | 19.0% |
| sokoban | Ordinary Hard | kinf_noncot |
download | model | dataset | 0.0% |
| sokoban | Ordinary Easy | k1_noncot |
download | model | dataset | 94.0% |
| sokoban | Ordinary Easy | k3_cot |
download | model | dataset | 95.0% |
| sokoban | Ordinary Easy | k3_noncot |
download | model | dataset | 92.0% |
| sokoban | Ordinary Easy | k5_cot |
download | model | dataset | 95.0% |
| sokoban | Ordinary Easy | k5_noncot |
download | model | dataset | 93.0% |
| sokoban | Ordinary Easy | k10_cot |
download | model | dataset | 94.0% |
| sokoban | Ordinary Easy | k10_noncot |
download | model | dataset | 90.0% |
| sokoban | Ordinary Easy | kinf_cot |
download | model | dataset | 91.0% |
| sokoban | Ordinary Easy | kinf_noncot |
download | model | dataset | 84.0% |
| maze2d | Ordinary Hard | k1_noncot |
download | model | dataset | 62.0% |
| maze2d | Ordinary Hard | k3_cot |
download | model | dataset | 59.0% |
| maze2d | Ordinary Hard | k3_noncot |
download | model | dataset | 54.0% |
| maze2d | Ordinary Hard | k5_cot |
download | model | dataset | 40.0% |
| maze2d | Ordinary Hard | k5_noncot |
download | model | dataset | 23.0% |
| maze2d | Ordinary Hard | k10_cot |
download | model | dataset | 21.0% |
| maze2d | Ordinary Hard | k10_noncot |
download | model | dataset | 2.0% |
| maze2d | Ordinary Hard | kinf_cot |
download | model | dataset | 3.0% |
| maze2d | Ordinary Hard | kinf_noncot |
download | model | dataset | 0.0% |
| maze2d | Ordinary Easy | k1_noncot |
download | model | dataset | 100.0% |
| maze2d | Ordinary Easy | k3_cot |
download | model | dataset | 87.0% |
| maze2d | Ordinary Easy | k3_noncot |
download | model | dataset | 100.0% |
| maze2d | Ordinary Easy | k5_cot |
download | model | dataset | 100.0% |
| maze2d | Ordinary Easy | k5_noncot |
download | model | dataset | 100.0% |
| maze2d | Ordinary Easy | k10_cot |
download | model | dataset | 93.0% |
| maze2d | Ordinary Easy | k10_noncot |
download | model | dataset | 100.0% |
| maze2d | Ordinary Easy | kinf_cot |
download | model | dataset | 96.0% |
| maze2d | Ordinary Easy | kinf_noncot |
download | model | dataset | 100.0% |
| pacman | Ordinary Hard | k1_noncot |
download | model | dataset | 84.0% |
| pacman | Ordinary Hard | k3_cot |
download | model | dataset | 38.0% |
| pacman | Ordinary Hard | k3_noncot |
download | model | dataset | 25.0% |
| pacman | Ordinary Hard | k5_cot |
download | model | dataset | 37.0% |
| pacman | Ordinary Hard | k5_noncot |
download | model | dataset | 1.0% |
| pacman | Ordinary Hard | k10_cot |
download | model | dataset | 7.0% |
| pacman | Ordinary Hard | k10_noncot |
download | model | dataset | 0.0% |
| pacman | Ordinary Hard | kinf_cot |
download | model | dataset | 6.0% |
| pacman | Ordinary Hard | kinf_noncot |
download | model | dataset | 0.0% |
| pacman | Two-Ghost | k1_noncot |
download | model | dataset | 78.0% |
| pacman | Two-Ghost | k3_cot |
download | model | dataset | 70.0% |
| pacman | Two-Ghost | k3_noncot |
download | model | dataset | 72.0% |
| pacman | Two-Ghost | k5_cot |
download | model | dataset | 62.0% |
| pacman | Two-Ghost | k5_noncot |
download | model | dataset | 69.0% |
| pacman | Two-Ghost | k10_cot |
download | model | dataset | 52.0% |
| pacman | Two-Ghost | k10_noncot |
download | model | dataset | 57.0% |
| pacman | Two-Ghost | kinf_cot |
download | model | dataset | 57.0% |
| pacman | Two-Ghost | kinf_noncot |
download | model | dataset | 48.0% |
| pacman | Easy Random-100 v1 | k1_noncot |
download | model | dataset | 97.0% |
| pacman | Easy Random-100 v1 | k3_cot |
download | model | dataset | 88.0% |
| pacman | Easy Random-100 v1 | k3_noncot |
download | model | dataset | 89.0% |
| pacman | Easy Random-100 v1 | k5_cot |
download | model | dataset | 81.0% |
| pacman | Easy Random-100 v1 | k5_noncot |
download | model | dataset | 82.0% |
| pacman | Easy Random-100 v1 | k10_cot |
download | model | dataset | 66.0% |
| pacman | Easy Random-100 v1 | k10_noncot |
download | model | dataset | 73.0% |
| pacman | Easy Random-100 v1 | kinf_cot |
download | model | dataset | 72.0% |
| pacman | Easy Random-100 v1 | kinf_noncot |
download | model | dataset | 58.0% |
| pacman | Easy Stratified-100 v2 | k1_noncot |
download | model | dataset | 96.0% |
| pacman | Easy Stratified-100 v2 | k3_cot |
download | model | dataset | 88.0% |
| pacman | Easy Stratified-100 v2 | k3_noncot |
download | model | dataset | 91.0% |
| pacman | Easy Stratified-100 v2 | k5_cot |
download | model | dataset | 80.0% |
| pacman | Easy Stratified-100 v2 | k5_noncot |
download | model | dataset | 85.0% |
| pacman | Easy Stratified-100 v2 | k10_cot |
download | model | dataset | 56.0% |
| pacman | Easy Stratified-100 v2 | k10_noncot |
download | model | dataset | 70.0% |
| pacman | Easy Stratified-100 v2 | kinf_cot |
download | model | dataset | 71.0% |
| pacman | Easy Stratified-100 v2 | kinf_noncot |
download | model | dataset | 60.0% |
| pusht | In-distribution | k1_noncot |
download | model | dataset | 86.0% |
| pusht | In-distribution | k3_cot |
download | model | dataset | 57.0% |
| pusht | In-distribution | k3_noncot |
download | model | dataset | 60.0% |
| pusht | In-distribution | k5_cot |
download | model | dataset | 46.0% |
| pusht | In-distribution | k5_noncot |
download | model | dataset | 45.0% |
| pusht | In-distribution | k10_cot |
download | model | dataset | 24.0% |
| pusht | In-distribution | k10_noncot |
download | model | dataset | 36.0% |
| pusht | In-distribution | kinf_cot |
download | model | dataset | 6.0% |
| pusht | In-distribution | kinf_noncot |
download | model | dataset | 24.0% |
| pusht | Near | k1_noncot |
download | model | dataset | 82.0% |
| pusht | Near | k3_cot |
download | model | dataset | 48.0% |
| pusht | Near | k3_noncot |
download | model | dataset | 46.0% |
| pusht | Near | k5_cot |
download | model | dataset | 42.0% |
| pusht | Near | k5_noncot |
download | model | dataset | 34.0% |
| pusht | Near | k10_cot |
download | model | dataset | 19.0% |
| pusht | Near | k10_noncot |
download | model | dataset | 20.0% |
| pusht | Near | kinf_cot |
download | model | dataset | 5.0% |
| pusht | Near | kinf_noncot |
download | model | dataset | 26.0% |
| pusht | Mid | k1_noncot |
download | model | dataset | 71.0% |
| pusht | Mid | k3_cot |
download | model | dataset | 38.0% |
| pusht | Mid | k3_noncot |
download | model | dataset | 21.0% |
| pusht | Mid | k5_cot |
download | model | dataset | 25.0% |
| pusht | Mid | k5_noncot |
download | model | dataset | 24.0% |
| pusht | Mid | k10_cot |
download | model | dataset | 9.0% |
| pusht | Mid | k10_noncot |
download | model | dataset | 12.0% |
| pusht | Mid | kinf_cot |
download | model | dataset | 1.0% |
| pusht | Mid | kinf_noncot |
download | model | dataset | 16.0% |
| pusht | Far (spatial OOD) | k1_noncot |
download | model | dataset | 31.0% |
| pusht | Far (spatial OOD) | k3_cot |
download | model | dataset | 9.0% |
| pusht | Far (spatial OOD) | k3_noncot |
download | model | dataset | 7.0% |
| pusht | Far (spatial OOD) | k5_cot |
download | model | dataset | 9.0% |
| pusht | Far (spatial OOD) | k5_noncot |
download | model | dataset | 0.0% |
| pusht | Far (spatial OOD) | k10_cot |
download | model | dataset | 3.0% |
| pusht | Far (spatial OOD) | k10_noncot |
download | model | dataset | 0.0% |
| pusht | Far (spatial OOD) | kinf_cot |
download | model | dataset | 2.0% |
| pusht | Far (spatial OOD) | kinf_noncot |
download | model | dataset | 3.0% |
Table2
| Task | Eval set | Model | Trajectory archive | Checkpoint | Eval data | Result |
|---|---|---|---|---|---|---|
| sokoban | 2-box Deadlock | van5k |
download | model | dataset | 22.0% |
| sokoban | 2-box Deadlock | always5k |
download | model | dataset | 60.0% |
| sokoban | 2-box Deadlock | bra5k |
download | model | dataset | 30.0% |
| sokoban | 3-box Deadlock | van5k |
download | model | dataset | 39.0% |
| sokoban | 3-box Deadlock | always5k |
download | model | dataset | 48.0% |
| sokoban | 3-box Deadlock | bra5k |
download | model | dataset | 39.0% |
| sokoban | 4-box Deadlock | van5k |
download | model | dataset | 27.0% |
| sokoban | 4-box Deadlock | always5k |
download | model | dataset | 24.0% |
| sokoban | 4-box Deadlock | bra5k |
download | model | dataset | 32.0% |
| sokoban | 2-box Structural Fork | van5k |
download | model | dataset | 85.0% |
| sokoban | 2-box Structural Fork | always5k |
download | model | dataset | 84.0% |
| sokoban | 2-box Structural Fork | bra5k |
download | model | dataset | 79.0% |
| sokoban | 3-box Structural Fork | van5k |
download | model | dataset | 34.0% |
| sokoban | 3-box Structural Fork | always5k |
download | model | dataset | 46.0% |
| sokoban | 3-box Structural Fork | bra5k |
download | model | dataset | 39.0% |
| sokoban | 4-box Structural Fork | van5k |
download | model | dataset | 22.0% |
| sokoban | 4-box Structural Fork | always5k |
download | model | dataset | 22.0% |
| sokoban | 4-box Structural Fork | bra5k |
download | model | dataset | 32.0% |
| pacman | Ordinary Hard | pacman_forward_v1 |
download | model | dataset | 6.0% |
| pacman | Two-Ghost | pacman_forward_v1 |
download | model | dataset | 54.0% |
| pacman | Forward Stress G8 | pacman_vanilla_kinf |
download | model | dataset | 78.0% |
| pacman | Forward Stress G8 | pacman_forward_v1 |
download | model | dataset | 78.0% |
| pacman | Forward Stress G8 | pacman_forward_v2 |
download | pending model publication | dataset | 64.0% |
| pacman | Forward Stress G12 | pacman_vanilla_kinf |
download | model | dataset | 9.0% |
| pacman | Forward Stress G12 | pacman_forward_v1 |
download | model | dataset | 4.0% |
| pacman | Forward Stress G12 | pacman_forward_v2 |
download | pending model publication | dataset | 6.0% |
Table3
| Task | Eval set | Model | Trajectory archive | Checkpoint | Eval data | Result |
|---|---|---|---|---|---|---|
| sokoban | 2-box Deadlock | van5k_rl90 |
download | model | dataset | 21.0% |
| sokoban | 2-box Deadlock | fwd3k_sft |
download | model | dataset | 41.0% |
| sokoban | 2-box Deadlock | fwd3k_rl90 |
download | model | dataset | 19.0% |
| sokoban | 2-box Deadlock | bra3k_sft |
download | model | dataset | 37.0% |
| sokoban | 2-box Deadlock | bra3k_rl90 |
download | model | dataset | 36.0% |
| sokoban | 3-box Deadlock | van5k_rl90 |
download | model | dataset | 42.0% |
| sokoban | 3-box Deadlock | fwd3k_sft |
download | model | dataset | 38.0% |
| sokoban | 3-box Deadlock | fwd3k_rl90 |
download | model | dataset | 38.0% |
| sokoban | 3-box Deadlock | bra3k_sft |
download | model | dataset | 35.0% |
| sokoban | 3-box Deadlock | bra3k_rl90 |
download | model | dataset | 44.0% |
| sokoban | 4-box Deadlock | van5k_rl90 |
download | model | dataset | 37.0% |
| sokoban | 4-box Deadlock | fwd3k_sft |
download | model | dataset | 25.0% |
| sokoban | 4-box Deadlock | fwd3k_rl90 |
download | model | dataset | 34.0% |
| sokoban | 4-box Deadlock | bra3k_sft |
download | model | dataset | 30.0% |
| sokoban | 4-box Deadlock | bra3k_rl90 |
download | model | dataset | 41.0% |
| sokoban | 2-box Structural Fork | van5k_rl90 |
download | model | dataset | 85.0% |
| sokoban | 2-box Structural Fork | fwd3k_sft |
download | model | dataset | 78.0% |
| sokoban | 2-box Structural Fork | fwd3k_rl90 |
download | model | dataset | 66.0% |
| sokoban | 2-box Structural Fork | bra3k_sft |
download | model | dataset | 84.0% |
| sokoban | 2-box Structural Fork | bra3k_rl90 |
download | model | dataset | 85.0% |
| sokoban | 3-box Structural Fork | van5k_rl90 |
download | model | dataset | 42.0% |
| sokoban | 3-box Structural Fork | fwd3k_sft |
download | model | dataset | 35.0% |
| sokoban | 3-box Structural Fork | fwd3k_rl90 |
download | model | dataset | 41.0% |
| sokoban | 3-box Structural Fork | bra3k_sft |
download | model | dataset | 33.0% |
| sokoban | 3-box Structural Fork | bra3k_rl90 |
download | model | dataset | 44.0% |
| sokoban | 4-box Structural Fork | van5k_rl90 |
download | model | dataset | 30.0% |
| sokoban | 4-box Structural Fork | fwd3k_sft |
download | model | dataset | 23.0% |
| sokoban | 4-box Structural Fork | fwd3k_rl90 |
download | model | dataset | 28.0% |
| sokoban | 4-box Structural Fork | bra3k_sft |
download | model | dataset | 22.0% |
| sokoban | 4-box Structural Fork | bra3k_rl90 |
download | model | dataset | 28.0% |
| sokoban | 2-box Deadlock | van5k_rl200 |
download | model | dataset | 22.0% |
| sokoban | 2-box Deadlock | fwd3k_rl200 |
download | model | dataset | 24.0% |
| sokoban | 2-box Deadlock | bra3k_rl200 |
download | model | dataset | 34.0% |
| sokoban | 3-box Deadlock | van5k_rl200 |
download | model | dataset | 44.0% |
| sokoban | 3-box Deadlock | fwd3k_rl200 |
download | model | dataset | 45.0% |
| sokoban | 3-box Deadlock | bra3k_rl200 |
download | model | dataset | 53.0% |
| sokoban | 4-box Deadlock | van5k_rl200 |
download | model | dataset | 38.0% |
| sokoban | 4-box Deadlock | fwd3k_rl200 |
download | model | dataset | 40.0% |
| sokoban | 4-box Deadlock | bra3k_rl200 |
download | model | dataset | 53.0% |
| sokoban | 2-box Structural Fork | van5k_rl200 |
download | model | dataset | 87.0% |
| sokoban | 2-box Structural Fork | fwd3k_rl200 |
download | model | dataset | 77.0% |
| sokoban | 2-box Structural Fork | bra3k_rl200 |
download | model | dataset | 84.0% |
| sokoban | 3-box Structural Fork | van5k_rl200 |
download | model | dataset | 44.0% |
| sokoban | 3-box Structural Fork | fwd3k_rl200 |
download | model | dataset | 47.0% |
| sokoban | 3-box Structural Fork | bra3k_rl200 |
download | model | dataset | 50.0% |
| sokoban | 4-box Structural Fork | van5k_rl200 |
download | model | dataset | 35.0% |
| sokoban | 4-box Structural Fork | fwd3k_rl200 |
download | model | dataset | 32.0% |
| sokoban | 4-box Structural Fork | bra3k_rl200 |
download | model | dataset | 45.0% |
| sokoban | 2-box Deadlock | van3k_rl2_step50 |
download | model | dataset | 29.0% |
| sokoban | 3-box Deadlock | van3k_rl2_step50 |
download | model | dataset | 34.0% |
| sokoban | 4-box Deadlock | van3k_rl2_step50 |
download | model | dataset | 28.0% |
| sokoban | 2-box Structural Fork | van3k_rl2_step50 |
download | model | dataset | 86.0% |
| sokoban | 3-box Structural Fork | van3k_rl2_step50 |
download | model | dataset | 34.0% |
| sokoban | 4-box Structural Fork | van3k_rl2_step50 |
download | model | dataset | 15.0% |
| sokoban | 2-box Deadlock | van3k_rl2_step100 |
download | model | dataset | 25.0% |
| sokoban | 3-box Deadlock | van3k_rl2_step100 |
download | model | dataset | 37.0% |
| sokoban | 4-box Deadlock | van3k_rl2_step100 |
download | model | dataset | 28.0% |
| sokoban | 2-box Structural Fork | van3k_rl2_step100 |
download | model | dataset | 86.0% |
| sokoban | 3-box Structural Fork | van3k_rl2_step100 |
download | model | dataset | 36.0% |
| sokoban | 4-box Structural Fork | van3k_rl2_step100 |
download | model | dataset | 18.0% |
| sokoban | 2-box Deadlock | van3k_rl2_step150 |
download | model | dataset | 24.0% |
| sokoban | 3-box Deadlock | van3k_rl2_step150 |
download | model | dataset | 39.0% |
| sokoban | 4-box Deadlock | van3k_rl2_step150 |
download | model | dataset | 39.0% |
| sokoban | 2-box Structural Fork | van3k_rl2_step150 |
download | model | dataset | 86.0% |
| sokoban | 3-box Structural Fork | van3k_rl2_step150 |
download | model | dataset | 37.0% |
| sokoban | 4-box Structural Fork | van3k_rl2_step150 |
download | model | dataset | 22.0% |
| sokoban | 2-box Deadlock | van3k_rl2_step200 |
download | model | dataset | 21.0% |
| sokoban | 3-box Deadlock | van3k_rl2_step200 |
download | model | dataset | 41.0% |
| sokoban | 4-box Deadlock | van3k_rl2_step200 |
download | model | dataset | 37.0% |
| sokoban | 2-box Structural Fork | van3k_rl2_step200 |
download | model | dataset | 86.0% |
| sokoban | 3-box Structural Fork | van3k_rl2_step200 |
download | model | dataset | 37.0% |
| sokoban | 4-box Structural Fork | van3k_rl2_step200 |
download | model | dataset | 23.0% |
| sokoban | 2-box Deadlock | van3k_rl3_step50 |
download | model | dataset | 28.0% |
| sokoban | 3-box Deadlock | van3k_rl3_step50 |
download | model | dataset | 40.0% |
| sokoban | 4-box Deadlock | van3k_rl3_step50 |
download | model | dataset | 35.0% |
| sokoban | 2-box Structural Fork | van3k_rl3_step50 |
download | model | dataset | 84.0% |
| sokoban | 3-box Structural Fork | van3k_rl3_step50 |
download | model | dataset | 39.0% |
| sokoban | 4-box Structural Fork | van3k_rl3_step50 |
download | model | dataset | 20.0% |
| sokoban | 2-box Deadlock | van3k_rl3_step100 |
download | model | dataset | 24.0% |
| sokoban | 3-box Deadlock | van3k_rl3_step100 |
download | model | dataset | 42.0% |
| sokoban | 4-box Deadlock | van3k_rl3_step100 |
download | model | dataset | 39.0% |
| sokoban | 2-box Structural Fork | van3k_rl3_step100 |
download | model | dataset | 84.0% |
| sokoban | 3-box Structural Fork | van3k_rl3_step100 |
download | model | dataset | 39.0% |
| sokoban | 4-box Structural Fork | van3k_rl3_step100 |
download | model | dataset | 28.0% |
| sokoban | 2-box Deadlock | van3k_rl3_step150 |
download | model | dataset | 18.0% |
| sokoban | 3-box Deadlock | van3k_rl3_step150 |
download | model | dataset | 45.0% |
| sokoban | 4-box Deadlock | van3k_rl3_step150 |
download | model | dataset | 42.0% |
| sokoban | 2-box Structural Fork | van3k_rl3_step150 |
download | model | dataset | 83.0% |
| sokoban | 3-box Structural Fork | van3k_rl3_step150 |
download | model | dataset | 44.0% |
| sokoban | 4-box Structural Fork | van3k_rl3_step150 |
download | model | dataset | 27.0% |
| sokoban | 2-box Deadlock | van3k_rl3_step200 |
download | model | dataset | 18.0% |
| sokoban | 3-box Deadlock | van3k_rl3_step200 |
download | model | dataset | 50.0% |
| sokoban | 4-box Deadlock | van3k_rl3_step200 |
download | model | dataset | 41.0% |
| sokoban | 2-box Structural Fork | van3k_rl3_step200 |
download | model | dataset | 82.0% |
| sokoban | 3-box Structural Fork | van3k_rl3_step200 |
download | model | dataset | 47.0% |
| sokoban | 4-box Structural Fork | van3k_rl3_step200 |
download | model | dataset | 27.0% |
Integrity
manifest.json records the source run identifier, summary metrics, remote archive path, byte size, file count, and SHA-256 digest when the archive was packaged by this release tool.
Table 2 uses the frozen six-set, 100-episode, max-40 execution contract. Table 3 currently tracks the matched pre-RL/RL90 max-40 evaluation; completed rows appear automatically when their run summary exists.
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