Update README.md

README.md

@@ -51,142 +51,50 @@ ProcessBench contains 12 diagnostic question families:
 
 ## Repository Contents
 
-This release is organized around a minimal reviewable benchmark package:
-
-- `splits/`: SFT and Eval QA entries.
-- `metadata/`: split statistics, task distribution, and license notes.
-- `examples/`: rendered representative task cards examples.
-- `ProcessData-SFT-Qwen/`: ProcessData-SFT-Qwen LoRA adapter weights and configurations.
-- `ProcessData-SFT-Qwen_results/`:  ProcessData-SFT-Qwen predictions and score summaries.
-- `benchmark_card.md`: benchmark-level documentation.
-- `croissant.json`: Croissant metadata with core and Responsible AI fields.
-
-Full upstream videos and full frame dumps are not redistributed in this release.
-
-## SFT-Eval Split Reconstruction
-
-### Relevant Assets
-
-- Public QA rows for `eval` and `sft`.
-- Split manifests and split counts.
-- Public release-relative references for each item.
-
-### How to use the public references
-
-Each row exposes three reconstruction-oriented fields:
-
-- `visual_ref`
-- `source_episode_ref`
-- `reconstruction_key_json`
-
-These are designed to be stable, path-free references. They are sufficient to map a released item back to the corresponding source episode or recording once you have obtained the upstream dataset under its original terms.
-
-### Source-specific units
-
-- `GM-100`: grouped by `(task_id, episode_id)`.
-- `RH20T`: grouped by `recording_id`.
-- `REASSEMBLE`: grouped by `recording_id`.
-- `AIST-Bimanual`: grouped by `recording_id`.
-
-### Expected workflow
-
-1. Obtain upstream datasets under their original terms.
-2. Use `source`, `source_task_id`, `source_unit_id`, `camera`, and `frame_indices_json` from the public release.
-3. Reconstruct the required visual inputs with the source-specific evaluation scripts in the main codebase.
-
-
-## Public QA fields Schema
-
-- `item_id`: Stable public item identifier.
-- `split`: `eval` or `sft`.
-- `source`: `GM-100`, `RH20T`, `REASSEMBLE`, or `AIST-Bimanual`.
-- `source_slug`: Short source slug used in release-relative references.
-- `source_task_id`: Source-side task identifier without local paths.
-- `source_unit_type`: Split-isolation unit type, e.g. `episode` or `recording`.
-- `source_unit_id`: Public unit identifier without local paths.
-- `task_id`: Canonical paper task ID `T1` ... `T12`.
-- `task_name`: Canonical paper task name.
-- `task_type_legacy`: Legacy engineering task name when it differs from paper naming.
-- `input_type`: Public input format description.
-- `question`: Public question text.
-- `choice_A` ... `choice_F`: Flattened answer choices.
-- `answer`: Public answer label in the release schema.
-- `answer_text`: Public answer text mapped from `answer`.
-- `num_choices`: Number of non-null answer choices.
-- `num_frames`: Number of referenced frames.
-- `frame_indices_json`: JSON-encoded frame indices.
-- `display_labels_json`: JSON-encoded panel labels such as `["X", "Y"]` or `["X", "Z", "Y"]`.
-- `camera`: Source camera identifier when available.
-- `arm_type`: Source-side arm configuration tag when available.
-- `visual_ref`: Release-relative visual reference string. This is not a local filesystem path.
-- `source_episode_ref`: Release-relative source unit reference.
-- `reconstruction_key_json`: Minimal JSON payload needed to reconstruct the sample with upstream data and source-specific scripts.
-- `task_meta_in_source`: Whether source-side task metadata/context exists upstream.
-- `task_meta_public`: Always `false` in this release build. Separate structured task-meta fields are intentionally withheld.
-- `split_version`: Current split version.
-- `split_group_id`: Source-side split group identifier.
-- `builder_version`: Public builder version tag.
-- `prompt_version`: Public prompt-serialization version tag.
-- `sft_target`: SFT-only supervised target string. Present only in `processdata_sft.*`.
-
-### Notes
-
-- `T5` is equivalent to `T_progress`.
-- `T8` is equivalent to `T_temporal`.
-- `T9` is equivalent to `T_binary`.
-- `T8` is normalized into six explicit permutation choices so the public table remains flat and Parquet-friendly.
-- `T9` is normalized to `A/B` choices even when the source data originally used `X/Y`.
-
-
-
-## Prompt Templates
-
-This file documents the public prompt serialization used by the current release build. Separate source-side task-meta prompting is intentionally disabled in this public release.
-
-### Standard multiple-choice template
+The release is organized as a compact, reviewable benchmark package:
 
 ```text
-{question}
-
-A: {choice_A}
-B: {choice_B}
-...
-
-Choose exactly one option label.
-
-Output protocol:
-- You may include brief reasoning before the final answer.
-- The final line must be exactly: <ANSWER>A</ANSWER>
-- Do not output anything after </ANSWER>.
+ProcessBench-Anom/
+├── splits/                         # SFT and Eval QA entries, split summaries
+│   ├── processdata_sft.jsonl
+│   ├── processdata_sft.parquet
+│   ├── sft_manifest.jsonl
+│   ├── processdata_eval.jsonl
+│   ├── processdata_eval.parquet
+│   └── eval-manifest.jsonl 
+
+│
+├── metadata/                       # statistics, schema, licenses, prompt templates, reconstruction notes
+│   ├── split_summary.json
+│   ├── task_distribution.csv
+│   ├── asset_licenses.csv
+│   ├── schema.md
+│   ├── prompt_templates.md
+│   └── reconstruction.md
+│
+├── examples/                       # rendered representative benchmark cards
+│   └── task_cards/
+│       ├── T1_phase_recognition.png
+│       ├── T2_contact_detection.png
+│       ├── ...
+│       └── T12_primitive_chain_restoration.png
+│
+├── ProcessData-SFT-Qwen/           # LoRA adapter weights and training configuration
+│   ├── adapter_config.json
+│   ├── adapter_model.safetensors
+│   ├── ...
+│   └── training_config.json
+│
+├── ProcessData-SFT-Qwen_results/   # predictions and summary of the post-trained model 
+│   ├── ProcessData-SFT-Qwen_predictions.json
+│   └── ProcessData-SFT-Qwen_summary.json
+│
+├── benchmark_card.md               # benchmark-level documentation
+├── croissant.json                  # Croissant core + Responsible AI metadata
+└── README.md
 ```
 
-### `T8` Temporal Ordering template
-
-```text
-You are shown 3 frames from a robot manipulation task.
-The frames are labeled X, Y, Z (these labels are arbitrary identifiers, not positional, and not time-ordered).
-Determine the correct chronological order of these frames (from earliest to latest).
-Choose exactly one 3-letter permutation, for example: YXZ means Y happened first, then X, then Z.
-
-Output protocol:
-- You may include brief reasoning before the final answer.
-- The final line must be exactly: <ANSWER>XYZ</ANSWER>
-- Do not output anything after </ANSWER>.
-```
-
-### `T9` Temporal Priority template
-
-```text
-A single comparison image shows two labeled robot-manipulation panels from the same episode.
-The left-right placement of the panels and the labels are arbitrary identifiers and do not indicate temporal order.
-Which labeled panel happened earlier in the real manipulation sequence, X or Y?
-Choose exactly one label: X or Y.
-
-Output protocol:
-- You may include brief reasoning before the final answer.
-- The final line must be exactly: <ANSWER>X</ANSWER>
-- Do not output anything after </ANSWER>.
-```
+Full upstream videos and full frame dumps are not redistributed in this release.
 
 
 ## License and Terms