Datasets:
Formats:
parquet
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
reinforcement-learning
llm
post-training
rlhf
open-source-software
mining-software-repositories
License:
Add RL Method Tracker v1.0 data
Browse files- README.md +116 -0
- landings.parquet +3 -0
- methods.parquet +3 -0
- papers.parquet +3 -0
- proposals.parquet +3 -0
README.md
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---
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license: cc-by-4.0
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pretty_name: RL Method Tracker
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language:
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- en
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size_categories:
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- 1K<n<10K
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tags:
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- reinforcement-learning
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- llm
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- post-training
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- rlhf
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- open-source-software
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- mining-software-repositories
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configs:
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- config_name: papers
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data_files: papers.parquet
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default: true
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- config_name: methods
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data_files: methods.parquet
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- config_name: landings
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data_files: landings.parquet
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- config_name: proposals
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data_files: proposals.parquet
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---
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# RL Method Tracker
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Which RL post-training methods for language models reached seven open-source training frameworks (verl, TRL, OpenRLHF, NeMo-RL, ROLL, slime, AReaL), when they landed, and how each framework offers them.
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Of 1,598 arXiv papers from January 2025 to June 2026 that propose a general RL training method, 37 reached the main branch of at least one framework.
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- Paper: [From RL Papers to Framework Code: Inclusion and Review in Seven Open-Source Training Frameworks](https://arxiv.org/abs/2610.28027)
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- Project page with search: https://pth2002.github.io/rl-method-tracker/
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- Code and the full data release: https://github.com/pth2002/rl-method-tracker
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- Archived release: [doi:10.5281/zenodo.23495744](https://doi.org/10.5281/zenodo.23495744)
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This is the frozen v1.0 data behind the report, with framework histories up to the 2026-10-18 snapshot.
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The GitHub repository refreshes the framework histories every week.
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## Load
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```python
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from datasets import load_dataset
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papers = load_dataset("Purdy0228/rl-method-tracker", "papers", split="train")
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methods = load_dataset("Purdy0228/rl-method-tracker", "methods", split="train")
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```
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## Subsets
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| Subset | Rows | One row per |
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|---|---|---|
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| `papers` | 6,939 | screened arXiv paper on RL for language models |
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| `methods` | 65 | method in the catalog, with its first landing in each framework |
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| `landings` | 101 | first commit that put a method on a framework's main branch |
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| `proposals` | 48 | public proposal for a general method that no framework included |
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### papers
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- `arxiv`, `title`, `month`: arXiv id, title and month of the first version.
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- `label`: what the paper contributes. `rl_method`, `rl_application`, `analysis`, `systems`, `distillation`, `preference_offline` or `other`.
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- `scope`: for RL methods, `general` when the method is the paper's main contribution and `embedded` when it sits inside a paper about a task, domain, agent or application.
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- `component`: the part of training the method changes, such as `advantage`, `clipping`, `sampling` or `entropy`.
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- `label_confidence`: `high`, `medium` or `low`.
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- `is_model_report`: the paper is the technical report of a model.
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- `general_method`: the paper counts toward the 1,598 general methods.
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- `included`: the paper's method reached the main branch of at least one framework.
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- `methods`: catalog ids of the included methods the paper introduces.
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- `n_frameworks_ever`, `n_frameworks_at_snapshot`: frameworks that ever included the method, and those that still include it at the snapshot.
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### methods
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- `id`, `name`, `family`, `arxiv`, `source_date`: the method and its first public source.
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- `n_fw_ever`, `n_fw_head`, `n_default`: frameworks that ever included it, that include it at the snapshot, and that turn it on by default.
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- `first_adoption`, `first_lag_days`, `first_lag_is_upper_bound`: date of the first landing in any framework and the days from the source to it. The lag is an upper bound when that first landing arrived with a repository's initial commit or a bulk release.
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- `n_self_contributed`: frameworks whose landing commit came from an author of the paper.
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- `<framework>_first`: date of the first landing in that framework.
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- `<framework>_head`: tier at the snapshot. `default` is on in a run that keeps every setting. `conditional_default` is on once a related feature is enabled. `core` is a selectable algorithm in the main code path. `option` is a switch that modifies the main algorithm. `experimental` and `recipe` sit outside the main path.
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### landings
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- `method`, `framework`, `date`, `pr`, `tier`: the landing and the pull request that made it.
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- `first_in_any`: this framework was the first to include the method.
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- `form`: how the method changes training, as `coefficient`, `term` or `pipeline`.
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- `commit_author_relation`: whether the landing commit came from an author of the paper.
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- `prior_request`: an issue or pull request asked for the method before it landed.
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- `pr_author`, `merged_by`, `author_prior_merger`, `self_merged`, `human_reviewers`: who proposed and merged the pull request. A prior merger had merged a pull request in the framework before.
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- `days_open`, `core_lines`, `files`, `lines`, `tests`, `docs`, `deps`, `new_files`: size and contents of the change.
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### proposals
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- `arxiv`, `method`, `framework`, `type`, `number`: the proposal, as a pull request (`pr`) or a request in an issue or discussion (`request`).
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- `outcome`: `open_no_reply`, `open_engaged`, `declined`, `redirected`, `stale_cleanup`, `closed_inactive`, `closed_no_comment` or `withdrawn`.
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- `reasons`: concerns the maintainers stated, such as `demand`, `surface`, `placement` or `evidence`.
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- `quote`: one short quote from the thread as evidence for the code.
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Thread texts stay on GitHub. The labelling rules and coding guides are in the [repository](https://github.com/pth2002/rl-method-tracker).
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## Citation
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```bibtex
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@misc{pan2026rlframeworks,
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title = {From {RL} Papers to Framework Code: Inclusion and Review in Seven Open-Source Training Frameworks},
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author = {Pan, Taiheng},
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year = {2026},
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eprint = {2610.28027},
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archivePrefix = {arXiv},
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primaryClass = {cs.LG},
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doi = {10.48550/arXiv.2610.28027},
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url = {https://arxiv.org/abs/2610.28027}
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}
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```
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## License
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CC BY 4.0. arXiv titles come from arXiv metadata.
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landings.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:4bb5c0566b24a5b8571ebacaf5a43066aa7cc78baf8d2eb6de507fecc0826faf
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size 20068
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methods.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:a159329ea062b3118e70169724efc4a849cbe74f535577460a0bab6e05b35609
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size 22415
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papers.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:def1928925e9bbfdbbfa94c13f597364feea652109dd97ec65a02387ce698ae3
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size 388484
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proposals.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:ec1ad7dfda87d5f553b78831ec0b53554a58dafc4d58eb6c0659b70a6547a9ac
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size 8945
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