Datasets:
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Error code: DatasetGenerationError
Exception: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table 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/json/json.py", line 281, in _generate_tables
examples = [ujson_loads(line) for line in batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
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 1694, 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 1880, 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.
event unknown | schema_version string | sequence int64 | source string | step_id int64 | timestamp string | trajectory_path string | trial_id string |
|---|---|---|---|---|---|---|---|
{
"message": "<permissions instructions>\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `danger-full-access`: No filesystem sandboxing - all commands are permitted. Network access is enabled.\nApproval policy is currently never. Do not provide the `sandbox_permissions` for any re... | 1.0 | 0 | system | 1 | 2026-09-01T12:46:27.084Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"message": "You are `/root`, the primary agent in a team of agents collaborating to fulfill the user's goals.\n\nAt the start of your turn, you are the active agent.\nYou can spawn sub-agents to handle subtasks, and those sub-agents can spawn their own sub-agents.\nAll agents in the team, including the agents that ... | 1.0 | 1 | system | 2 | 2026-09-01T12:46:27.084Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"message": "<multi_agent_mode>Any earlier instruction enabling proactive multi-agent delegation no longer applies. Do not spawn sub-agents unless the user or applicable AGENTS.md/skill instructions explicitly ask for sub-agents, delegation, or parallel agent work.</multi_agent_mode>",
"source": "system",
"step_... | 1.0 | 2 | system | 3 | 2026-09-01T12:46:27.085Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"message": "<environment_context>\n <cwd>/workspace</cwd>\n <shell>bash</shell>\n <current_date>2026-09-01</current_date>\n <timezone>Etc/UTC</timezone>\n <filesystem><workspace_roots><root>/workspace</root></workspace_roots><permission_profile type=\"disabled\"><file_system type=\"unrestricted\" /></permissio... | 1.0 | 3 | user | 4 | 2026-09-01T12:46:27.085Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"message": "# Write up the research idea into a complete paper\n\nYour goal is to write up the following idea into a complete scientific paper:\n\n```markdown\nThe research overview is in `/workspace/materials/research_overview.md`; read it in full before starting.\n```\n\nNote that the overview represents a prelim... | 1.0 | 4 | user | 5 | 2026-09-01T12:46:27.118Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"extra": {
"api_call_id": "api_call_1",
"codex_turn_id": "01a05d01-aca0-7fc0-9a99-705d37025ce5",
"tool_call_details": {
"call_NOz3RikYL9ro3cL3AUNZREqF": {
"raw_arguments": "const r = await tools.exec_command({cmd:\"pwd && rg --files materials | sort && printf '\\\\n--- template size ---\\\... | 1.0 | 5 | agent | 6 | 2026-09-01T12:46:44.881Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"extra": {
"api_call_id": "api_call_2",
"codex_turn_id": "01a05d01-aca0-7fc0-9a99-705d37025ce5",
"tool_call_details": {
"call_RQxuKHm4KIIgDhM3MgzqHdDD": {
"raw_arguments": "const paths = [\"materials/AGENTS.md\",\"materials/template.tex\",\"materials/research_overview.md\",\"materials/tabl... | 1.0 | 6 | agent | 7 | 2026-09-01T12:46:51.700Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"extra": {
"api_call_id": "api_call_3",
"codex_turn_id": "01a05d01-aca0-7fc0-9a99-705d37025ce5",
"tool_call_details": {
"call_IrbgmN2HmDqwtNHKg5b6zUBL": {
"raw_arguments": "const paths = [\"materials/tables/table_im.tex\",\"materials/tables/table_le.tex\",\"materials/tables/table_rr.tex\",... | 1.0 | 7 | agent | 8 | 2026-09-01T12:47:00.602Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"extra": {
"api_call_id": "api_call_4",
"codex_turn_id": "01a05d01-aca0-7fc0-9a99-705d37025ce5",
"tool_call_details": {
"call_012Zk0IpqD5RJOpdifzYx1IF": {
"raw_arguments": "const r = await tools.exec_command({cmd:\"sed -n '281,420p' materials/code/scripts/train_vlm_multi.sh && printf '\\\\... | 1.0 | 8 | agent | 9 | 2026-09-01T12:47:11.395Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"extra": {
"api_call_id": "api_call_5",
"codex_turn_id": "01a05d01-aca0-7fc0-9a99-705d37025ce5",
"tool_call_details": {
"call_buPrRWWy6y9oVxYMeGFwEMIa": {
"raw_arguments": "const cmds = [\n \"nl -ba materials/code/openrlhf/datasets/prompts_dataset.py | sed -n '1,270p'\",\n \"nl -ba mater... | 1.0 | 9 | agent | 10 | 2026-09-01T12:47:21.502Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
{
"extra": {
"api_call_id": "api_call_6",
"codex_turn_id": "01a05d01-aca0-7fc0-9a99-705d37025ce5",
"tool_call_details": {
"call_JurGxQfqHev7qVDInyJG9xAV": {
"raw_arguments": "const cmds = [\n \"nl -ba materials/code/openrlhf/trainer/ppo_utils/replay_buffer.py | sed -n '397,530p'\",\n \"nl ... | 1.0 | 10 | agent | 11 | 2026-09-01T12:47:31.841Z | agent/trajectory.json | 6c45b4f4-d767-4adf-90b5-a59bcc300298 |
Paper-Writing Exam Agent Trials
This is a public archive of complete agent trials run on the public
Jack-Jieke-Wu/Paper-Writing-Exam benchmark. It contains sanitized trajectories,
agent outputs, final papers, Harbor results, verifier metrics, and agent-specific
diagnostics.
The repository is public by design. Access to this repository does not permit redistribution of the benchmark, model outputs, or third-party source material. Every upload must still pass the local fail-closed exporter checks.
Layout
README.md
data/
βββ trials.jsonl
βββ events.jsonl
βββ trials.schema.json
βββ events.schema.json
artifacts/
βββ <trial-id>.tar.gz
manifests/
βββ release.json
βββ <trial-id>.json
data/trials.jsonl has one record per Harbor trial. data/events.jsonl has one
record per step derived from Harbor's native ATIF files
(agent/trajectory*.json). The compressed archive contains the original ATIF
trajectories, allowlisted submission, agent logs/checkpoints, Harbor
result.json, and verifier evaluation.json.
For Harbor v0.20.0, accepted native trajectory versions are
ATIF-v1.0 through ATIF-v1.7; local file-based subagent references must
resolve to included trajectory files.
Archives retain Harbor's native agent/, verifier/, steps/, and
artifacts/ directories so single-step and multi-step trials remain
reconstructable.
Saving A New Trial
harbor run writes a trial locally; it does not upload the result here. From
the paperbench-harbor repository, export one completed Harbor trial with the
sanitizing exporter:
python3 scripts/export_trial.py \
--trial-dir /path/to/harbor-jobs/<job-name>/<trial-id> \
--output-dir /path/to/Paper-Writing-Exam-Trials \
--private-manifest /path/to/task/tests/private/source_manifest.json \
--task-id pwb-0001 \
--benchmark PaperWrite-Bench \
--protocol short \
--benchmark-hf-revision <immutable-benchmark-commit> \
--harbor-repo-commit <paperbench-harbor-commit> \
--agent-name codex \
--agent-version <agent-version> \
--integration-commit <integration-commit> \
--model <provider>/<model> \
--provider <provider> \
--agent-config-file /path/to/non-secret-agent-config.json
The exporter creates artifacts/<trial-id>.tar.gz,
manifests/<trial-id>.json, and appends a record to data/trials.jsonl. When
the trial contains ATIF events, it also appends their one-event-per-step index
to data/events.jsonl. It performs the credential/private-file checks before
committing those outputs. Inspect the result, then upload the staging
directory separately:
hf upload Jack-Jieke-Wu/Paper-Writing-Exam-Trials \
/path/to/Paper-Writing-Exam-Trials . \
--repo-type dataset \
--exclude '.git/**' \
--commit-message "Add trial <trial-id>"
Record the immutable commit SHA returned by this upload as
TRIAL_DATASET_REVISION; use that value in the viewing commands below.
The full workflow, including how to choose --jobs-dir, is documented in the
source repository's docs/trial-dataset.md.
View One Trial
Use the trial ID from data/trials.jsonl, then download its summary and
manifest without downloading every archive:
TRIAL_ID=<trial-id>
TRIAL_DATASET_REVISION=<40-character-Hugging-Face-commit>
VIEW_DIR=/tmp/paper-writing-trial
mkdir -p "$VIEW_DIR"
hf download Jack-Jieke-Wu/Paper-Writing-Exam-Trials \
data/trials.jsonl \
"manifests/$TRIAL_ID.json" \
--repo-type dataset \
--revision "$TRIAL_DATASET_REVISION" \
--local-dir "$VIEW_DIR"
If data/events.jsonl exists in the selected release, download it separately
to inspect the one-event-per-step index.
To view the complete trajectory and final output, download and unpack the single archive:
hf download Jack-Jieke-Wu/Paper-Writing-Exam-Trials \
"artifacts/$TRIAL_ID.tar.gz" \
--repo-type dataset \
--revision "$TRIAL_DATASET_REVISION" \
--local-dir "$VIEW_DIR"
mkdir -p "$VIEW_DIR/unpacked"
tar -xzf "$VIEW_DIR/artifacts/$TRIAL_ID.tar.gz" -C "$VIEW_DIR/unpacked"
Then inspect:
$VIEW_DIR/unpacked/agent/trajectory*.json # single-step trajectory
$VIEW_DIR/unpacked/steps/*/agent/trajectory*.json # multi-step trajectories
$VIEW_DIR/unpacked/artifacts/workspace/submission/ # single-step output
$VIEW_DIR/unpacked/steps/*/artifacts/workspace/submission/ # multi-step output
$VIEW_DIR/unpacked/harbor/result.json
$VIEW_DIR/unpacked/verifier/evaluation.json
data/events.jsonl is a one-event-per-step index derived from the original
Harbor ATIF trajectory. The original trajectory and agent logs are preserved in
the archive.
Provenance
Each trial references the benchmark without duplicating its task tree using:
benchmark_hf_repoand immutablebenchmark_hf_revision;task_idandtask_checksum;harbor_repo_commit;agent_name,agent_version, andintegration_commit;- model/provider and a hash of non-secret configuration;
- Harbor reward, official metrics, timing, and artifact SHA-256.
Exports require the task's verifier-only tests/private/source_manifest.json
and a SHA-256 hash of the non-secret agent configuration (or a configuration
file from which that hash can be computed).
The exporter compares source-material hashes before writing any output, and
does not copy that manifest into this repository.
Security and privacy
The exporter rejects API keys, bearer tokens, cookies, credential files, host
credentials, encoded credentials, solution/, tests/private/,
eval_points.json, ground-truth papers, and unrelated host files. It scans a
single temporary source snapshot, then derives the archive, event index, and
manifest from that same snapshot. It does not upload task containers or publish
from inside an evaluated container.
Do not upload raw environment files, authentication state, prompts containing secrets, or data that the benchmark license does not permit you to retain. Review every generated manifest before uploading it to this public repository.
Schemas are stored in data/*.schema.json. The local exporter and its tests are
maintained at:
- Downloads last month
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