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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type int64 to null
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2059, in cast_array_to_feature
                  _c(array.field(name) if name in array_fields else null_array, subfeature)
                  ~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
                  return array_cast(
                      array,
                  ...<2 lines>...
                      allow_decimal_to_str=allow_decimal_to_str,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2005, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type int64 to null

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CooperBench flash_10 evaluation traces

Every run here is the same frozen contract: subset flash_10 (10 pairs / 10 tasks / 9 repos), agent mini_swe_agent_v2, setting coop + --git, Modal sandboxes, step_limit=200, max_model_len=49152. Produced by scripts/eval_e2e.py in CooperTrain. Two runs are comparable only if their run_meta.json agree — check it rather than assuming.

Each run directory contains, per pair:

file contents
agentN_traj.json one agent's trajectory, post-compaction window only
agentN_full_traj.json the full history under segments[]; use kind=="solver" (the summarizer segments are near-duplicates and double-count)
agentN.patch the graded artifact — the diff taken from that agent's PR
eval.json merge status and per-feature pass/fail
result.json agent exit statuses, duration, message counts
summary.json pairs and features passed
run_meta.json the full contract this run used

Submission is a PR, not a patch file. Since cooperbench 0.0.28 the agent opens its own PR and grading reads git ls-remote --tags team refs/tags/pr/<agent>. The log line no patch.txt to publish is a legacy message, not a failure — an empty patch means no PR was opened. Before reading a 0/10 as a model result, grep the trajectories for gh: command not found.

The runs

Model baselines — no injected context

run model pairs features
flash10-qwen3-5-9b, BASELINE-9b-noctx-backup Qwen3.5-9B 2/10 7/20
flash10-qwen3-6-35b-a3b Qwen3.6-35B-A3B 2/10 7/20
flash10-qwen3-5-122b Qwen3.5-122B-A10B 3/10 10/20

The 27B base (4/10) was overwritten: eval_e2e.py derives the run name from the model, so the 27B ceiling run reused flash10-qwen3-5-27b. That directory now holds the 9/10 ceiling. The script now refuses to overwrite a finished run.

Teacher-context ceilings

Each injects a block into every agent's own feature.md, then restores the originals. The question each answers is what a teacher could know that a student could not.

run injected context pairs features
flash10-qwen3-5-27b protocol + role + the benchmark's gold patch 9/10 18/20
ceiling-ctx-9b same, on the 9B 5/10 11/20
ceiling-protocol-only-27b per-task workflows — no diff block, but still names files, line numbers and hidden-test content 7/10 16/20
ceiling-protocol-only-9b same, on the 9B 1/10 8/20
ceiling-backlog-27b shared-backlog protocol — generic, no task content 4/10 13/20
ceiling-negotiate-27b negotiate-your-own — a menu of 10 protocols plus a decision rule, no task content 4/10 13/20

The headline: every context that beats base contains the answer. Both purely procedural protocols score exactly what the unbriefed model scores — while demonstrably working (ceiling-negotiate-27b produced 7 identical merges out of 10, the most of any run, and ceiling-backlog-27b produced 10 clean merges with 0 conflicts).

On-policy distillation students

LoRA r=32 over Qwen3.5-9B, trained by coopertrain/opd/. Base to beat is 2/10, 7/20.

run teacher pairs features
flash10-qwen3-5-9b-opd-r1 27B + gold patch, 1 epoch 0/10 3/20
flash10-qwen3-5-9b-opd-self same 9B weights + gold patch, 1 epoch 0/10 1/20
flash10-qwen3-5-9b-opd-proto 27B + per-task workflows, 3 epochs 1/10 4/20

Void — do not use

VOID-opd-self-gh-broken ran against cooperbench 0.0.22 rather than 0.0.28: eval_e2e.py invoked the CLI by name and PATH resolved it to a second install. 0.0.22 names the shared daemon team, leaves real GitHub as origin, installs no gh shim and grades cat patch.txt. All 19 agents hit gh: command not found, pushed correct commits to team/agentN, and were scored empty. Kept only as a worked example of the failure.

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