Gyubeum/AndroidFlux_RL_Train
AndroidFlux RL — policy prompts Slice Prompts Source t_minus_n 2,459 AndroidFlux source trajectories successful 2,623 AndroidFlux source trajectories t_minus_1 2,459 AndroidFlux source trajectories t 2,459 AndroidFlux source trajectories Subtotal 10,000 ui_genie 10,000 UI-Genie reward-model prompts (5,000-prompt core marked by in_reduced) The four AndroidFlux slices are drawn from replayed source trajectories. The successful slice contains 53… See the full description on the dataset page: https://huggingface.co/datasets/Gyubeum/AndroidFlux_RL_Train.
AndroidFlux RL — policy prompts
The four AndroidFlux slices are drawn from replayed source trajectories. The successful slice contains 53 final-action decisions (2.02%), 53 penultimate-action decisions (2.02%), and 2,517 earlier decisions. These positions refer to the action the policy generates; the last history action is one step earlier. Environment success and canonical train membership are verified.
All 20 canonical unseen-test task types are excluded from them. Seen-test instances remain in the error-derived slices, explicitly marked in provenance.jsonl. The two newly added tminusn checkpoints are confirmed train. These split rules are about AndroidWorld task types and so do not apply to ui_genie, whose contexts come from a different corpus.
Every slice has samples.parquet, context.parquet, images (one images.parquet, or images-NNNNN-of-NNNNN.parquet shards where the screenshot set is large), samples.json, provenance, and validation/manifests. The Parquet schemas follow data_from_rm_eval, adapted to prompt-only system/user conversations with nullable candidate/preference fields. The t slice also has 17,213 unlabelled recovery candidate slots (seven per context), with donor provenance preserved. Per-slice deviations from the reference layout are listed in each build_manifest.json.
The ui_genie slice is a separate 10,000-prompt release drawn from `Gyubeum/UI_Genie_128k` rather than from AndroidFlux trajectories: stratified over history length, reference action type and domain, then filtered by a base-policy rollout whose candidates the reward model had to be able to order. It ships the history screenshots the reward model reads, and the four AndroidFlux slices now also ship their restored history screenshots. See `ui_genie/SAMPLING.md`, and `ui_genie/CONTRIBUTING_FORMAT.md` for the structured format to send new recovery contexts in.
AndroidFlux context repair — 2026-09-14
The original 10,000 AndroidFlux prompt IDs, splits, successful position quotas and t recovery candidates are unchanged. All four slices now embed their full history screenshots, retain clean source-derived or deterministic natural-language action histories alongside the original raw text, and expose recorded next-action references with availability and provenance. References are not verified GT and their coordinates remain source-native. Policy input stays current-image-only; RM readers use context image links or the chronological rm_image_ids (last at most five screens). See per-slice READMEs and repair_validation_summary.json for exact coverage and limitations.
The additive v2 columns extend (rather than exactly match) the original reference schema. The existing ui_genie/ release is untouched. androidflux_tools/export_repaired_interchange.py produces the documented portable GRPO interchange directly from each repaired Parquet slice, without any original trajectory paths.