AutoResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery
Paper • 2604.25256 • Published • 31
Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowTypeError
Message: ("Expected bytes, got a 'int' object", 'Conversion failed for column metadata with type object')
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Missing a name for object member. in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4523, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2768, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2972, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2483, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 331, in _generate_tables
pa_table = pa.Table.from_pandas(df, preserve_index=False)
File "pyarrow/table.pxi", line 4768, in pyarrow.lib.Table.from_pandas
File "/usr/local/lib/python3.14/site-packages/pyarrow/pandas_compat.py", line 651, in dataframe_to_arrays
arrays = [convert_column(c, f)
~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/pyarrow/pandas_compat.py", line 639, in convert_column
raise e
File "/usr/local/lib/python3.14/site-packages/pyarrow/pandas_compat.py", line 633, in convert_column
result = pa.array(col, type=type_, from_pandas=True, safe=safe)
File "pyarrow/array.pxi", line 390, in pyarrow.lib.array
File "pyarrow/array.pxi", line 91, in pyarrow.lib._ndarray_to_array
check_status(NdarrayToArrow(pool, values, mask, from_pandas,
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowTypeError: ("Expected bytes, got a 'int' object", 'Conversion failed for column metadata with type object')Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AutoResearchBench
Project Page | Paper | GitHub
This repository hosts the obfuscated benchmark bundle for AutoResearchBench, a dedicated benchmark for autonomous scientific literature discovery.
AutoResearchBench consists of two complementary task types:
- Deep Research: requires tracking down a specific target paper through a progressive, multi-step probing process.
- Wide Research: requires comprehensively collecting a set of papers satisfying given conditions.
The published file uses public reversible obfuscation for benchmark release. It lowers casual web exposure, but it is not strong access control. Please do not repost decrypted questions or answers in plain text or images online.
Quick Start
1. Download the released bundle
export HF_TOKEN=your_hf_token # required if this dataset repo is private
mkdir -p input_data
curl -L \
-H "Authorization: Bearer ${HF_TOKEN}" \
-o input_data/AutoResearchBench.jsonl.obf.json \
https://huggingface.co/datasets/Lk123/AutoResearchBench/resolve/main/AutoResearchBench.jsonl.obf.json
2. Decrypt it locally
Use decrypt_benchmark.py from the GitHub repository:
python3 decrypt_benchmark.py \
--input-file input_data/AutoResearchBench.jsonl.obf.json \
--output-file input_data/AutoResearchBench.jsonl
Run inference and evaluation on the decrypted AutoResearchBench.jsonl, not on the .obf.json bundle directly.
3. Usage
After installing dependencies and configuring your .env as described in the code repository, you can run inference:
bash run_inference.sh
❤️ Citing Us
If you find this repository or our work useful, please consider giving a star ⭐ and or citing our work, which would be greatly appreciated:
@misc{xiong2026autoresearchbenchbenchmarkingaiagents,
title={AutoResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery},
author={Lei Xiong and Kun Luo and Ziyi Xia and Wenbo Zhang and Jin-Ge Yao and Zheng Liu and Jingying Shao and Jianlyu Chen and Hongjin Qian and Xi Yang and Qian Yu and Hao Li and Chen Yue and Xiaan Du and Yuyang Wang and Yesheng Liu and Haiyu Xu and Zhicheng Dou},
year={2026},
eprint={2604.25256},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2604.25256},
}
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