Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning
Paper
•
2601.06943
•
Published
•
184
Datasets:
Dataset Viewer
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: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0xf9 in position 34: invalid start byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2431, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 329, in __iter__
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/csv/csv.py", line 188, in _generate_tables
csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 1199, in xpandas_read_csv
return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
return _read(filepath_or_buffer, kwds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 620, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
self._engine = self._make_engine(f, self.engine)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
return mapping[engine](f, **self.options)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
self._reader = parsers.TextReader(src, **kwds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pandas/_libs/parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
File "pandas/_libs/parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
File "<frozen codecs>", line 322, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xf9 in position 34: invalid start byteNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
VideoDR: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning
VideoDR is the first video deep research benchmark, designed to evaluate the capability of Multimodal Large Language Models (MLLMs) to perform complex reasoning based on video content while leveraging the Open Web.
In real-world video question answering scenarios, videos often provide only localized visual cues, while verifiable answers are distributed across the open web. VideoDR requires models to jointly perform cross-frame clue extraction, iterative retrieval, and multi-hop reasoning-based verification.
Core Capabilities
VideoDR evaluates agents based on three core pillars:
- 🎞️ Multi-frame Visual Cues: Accurately identifying continuous key information from multiple video frames.
- 🌍 Interactive Search: Interacting with a browser environment to perform multi-hop deep search.
- 🧩 Evidence Synthesis: Combining video clues and web evidence to provide a verifiable factual answer.
The benchmark spans six semantic domains and includes high-quality samples obtained through rigorous human annotation and quality control.
Failure Analysis
The official repository provides an LLM-based failure analysis tool (llm_as_judge) to automatically classify failure cases into different error categories based on trace analysis. This helps in identifying core bottlenecks such as goal drift and long-horizon consistency in video agents.
Citation
If you find this benchmark useful for your research, please cite:
@article{liu2026watching,
title={Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning},
author={Liu, Chengwen and Yu, Xiaomin and Chang, Zhuoyue and Huang, Zhe and Zhang, Shuo and Lian, Heng and Wang, Kunyi and Xu, Rui and Hu, Sen and Hou, Jianheng and others},
journal={arXiv preprint arXiv:2601.06943},
year={2026}
}
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