| --- |
| license: other |
| pretty_name: Into the Unknown |
| license_name: mixed |
| license_link: LICENSE |
| tags: |
| - agents |
| - ai-scientist |
| - scientific-discovery |
| - benchmark |
| task_categories: |
| - text-generation |
| configs: |
| - config_name: benchmark |
| data_files: benchmark/index.csv |
| - config_name: outcomes |
| data_files: outcomes/index.csv |
| - config_name: trajectories |
| data_files: trajectories/index.csv |
| --- |
| |
| # Into the Unknown |
|
|
| **Dataset Summary** |
|
|
| Into the Unknown tests whether AI agents can build on a scientist's work and write a follow-up paper. Each of its 15 tasks gives an agent a published (or recently submitted) paper and a follow-up research direction proposed by the paper's own author; the agent must carry out the research and write a follow-up paper that is honest, complete, and meets the scientist's bar. |
|
|
| This dataset holds the 15 tasks and everything nine agents produced on them: 135 submissions, with each agent's paper, full trajectory, and the files it wrote. Code, rubrics and graders are on [GitHub](https://github.com/prometheus-eval/into-the-unknown); the paper is on [arXiv](https://arxiv.org/abs/2610.19159). |
|
|
| **Supported Tasks and Leaderboards** |
|
|
| The task is open-ended research: given the paper and the direction, produce the follow-up paper. The [leaderboard](https://prometheus-eval.github.io/into-the-unknown/viewer/#/) shows every agent's results and every rubric verdict, and you can [submit your agent's paper](https://prometheus-eval.github.io/into-the-unknown/viewer/#/submit) to be evaluated. |
|
|
| **Subsets** |
|
|
| | subset | content | |
| |---|---| |
| | `benchmark/` | The 15 tasks: `paper<i>/task_spec.md`, the original paper (`paper.pdf`, its text `paper.md`, figures `images/`) and `index.csv`. A task's code and data are downloaded by `prepare_tasks.py` in the GitHub repository. | |
| | `outcomes/` | The papers the agents wrote, `<agent>/paper<i>.pdf` (the `proposal/report.pdf` the judge read): 131 PDFs, since four GLM-5.3 runs produced none. | |
| | `trajectories/` | Each run's `<agent>/paper<i>.json` (run metadata and every agent event), plus the harnesses' own logs (`*.harness_logs.tar`; DeepSeek-V4-Pro's full conversation is here) and the runners' console logs (`*.runner_logs.tar`). | |
| | `file_systems/` | Each submission's files as the judge saw them: `proposal/` and the rest of the working directory (`workdir_outside_proposal/`), without environments, caches or the final transcript. `view.tar.part-*` with a SHA-256 `manifest.json`; nine runs add a `supplement.tar` of files the judge's copy lacked. | |
|
|
| Agents (`<agent>`): `opus-4.8`, `opus-5`, `opus-5.5`, `fable-5`, `sol-5.6`, `astra-6`, `deepseek-v4-pro`, `kimi-k3`, `glm-5.3`. |
|
|
| **Dataset Structure** |
|
|
| An example of a `benchmark` datum is as follows: |
|
|
| ``` |
| paper: (str) - The task id, P1 to P15. |
| group: (str) - A: published 2024 or earlier; B: submitted 2026. |
| title: (str) - The original paper's title. |
| domain, venue, lab: (str) - Its field, venue and the laboratory of its authors. |
| citations: (int) - Citations as of September 14, 2026. |
| original_paper: (str) - A link to the original paper. |
| follow_up_direction: (str) - The research direction the paper's author proposed. |
| task_spec, paper_pdf, paper_md: (str) - Paths to the task specification and the original paper in this dataset. |
| ``` |
|
|
| `outcomes/index.csv` and `trajectories/index.csv` list one row per submission (agent, paper, file, and run metadata). |
|
|
| **Evaluation** |
|
|
| Run an agent and judge its submission with the [GitHub repository](https://github.com/prometheus-eval/into-the-unknown): |
|
|
| ```bash |
| bash src/solver/run.sh <agent> <paper_id> |
| python src/grader/run_codex_judge.py prepare --agents <agent> # then rescope, launch |
| ``` |
|
|
| To unpack one submission's files: |
|
|
| ```bash |
| huggingface-cli download prometheus-eval/into-the-unknown --repo-type dataset \ |
| --include "file_systems/astra-6/paper3/*" --local-dir . |
| cd file_systems/astra-6/paper3 && cat view.tar.part-* > view.tar && tar -xf view.tar |
| ``` |
|
|
| **Sample Usage** |
|
|
| Load the benchmark subset directly with the `datasets` library: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| tasks = load_dataset('prometheus-eval/into-the-unknown', 'benchmark', split='train') |
| ``` |
|
|
| A few notes specific to this dataset: |
|
|
| - `outcomes/fable-5/paper8.pdf` has a real person's name, affiliation and e-mail blacked out on its title page; every other PDF is byte-identical to the submission. |
| - Files written on the compute cluster can contain absolute paths of the cluster's file system. |
| - In `file_systems/opus-5.5/paper12`, two R help pages (`qsreg.html`, `spam.html`) differ only in case from other pages; the archive has the originals, the others are in `supplement.tar`, and `manifest.json` lists both under `checked_against_judge_record.sha256_mismatch`. |
|
|
| **Citation** |
|
|
| If you find our work helpful, please consider citing it: |
|
|
| ```bibtex |
| @article{kim2026into, |
| title={Into the Unknown: Benchmarking AI agents on open scientific research problems}, |
| author={Kim, Seungone and Geng, Jiayi and Lee, Young-Jun and Liu, Bo and Suk, Juyoung and Lubbers, Nicholas and Wood, Mitchell and Noack, Marcus and Yao, Yong-Xin and Shi, Yuan and others}, |
| journal={arXiv preprint arXiv:2610.19159}, |
| year={2026} |
| } |
| ``` |
|
|
| **License** |
|
|
| Task specifications, rubrics and documentation are released under the Apache-2.0 license of the GitHub repository. The original papers in `benchmark/` remain under their authors' and publishers' terms and are included for research use; agent outputs may contain third-party code and data that keep their own licenses. |
