held-out 20: benchmark spec, prescriptive camera rig, eval seeds, Franka index

.gitattributes

@@ -60,3 +60,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
 stage1_5k_camera_fixed/artifacts/awr_weights_phase.json filter=lfs diff=lfs merge=lfs -text
 stage1_5k_camera_fixed/artifacts/awr_weights_v2.json filter=lfs diff=lfs merge=lfs -text
+franka/index/heldout20_index.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,140 @@
 ---
-license: mit
+license: apache-2.0
+task_categories:
+- robotics
+tags:
+- robotics
+- manipulation
+- few-shot
+- cross-embodiment
 ---
+
+# AXIS held-out 20 — a cross-embodiment few-shot adaptation benchmark
+
+20 tasks never seen in pretraining, 20 demonstrations each, LoRA adaptation, rollout evaluation.
+
+**This release is the SPECIFICATION and the INDEX, not the demonstration data.** It is published
+first and on purpose: everything here is what you need to *render* the benchmark on your own
+embodiment, and none of it depends on our video encoding being finished.
+
+> **Status: the task list is CANDIDATES.** The learnability gate (below) has not run yet. It can
+> only remove tasks, never add them, so treat the 20 as an upper bound on the final set.
+
+## What is being measured
+
+Few-shot adaptation to a target setup — **not** generalisation. A policy gets 20 demonstrations of
+an unseen task, adapts by LoRA, and is evaluated on that same task under **the same conditions the
+demonstrations contain**.
+
+That last clause decides a question that is otherwise answered wrongly. Measured from the
+demonstration data itself:
+
+| axis | varies across demos? | so at eval |
+|---|---|---|
+| object identity, placement, jitter | **yes** | vary |
+| robot initial state | **no** — 0.22° / 1.8 mm across 856 and 1,148 episodes | **fix** |
+| camera pose | **no** | **fix** |
+| appearance / lighting / texture | **no** — the randomisation config holds position deltas only | **fix** |
+
+Randomising something at eval that the demos never contain measures a regime the benchmark does
+not train for, and produces a number that answers no one's question.
+
+## Layout
+
+```
+spec/
+  benchmark_spec.json    task list, operations, gate thresholds, protocol
+  camera_rig.json        the REQUIRED wrist rig, and our measured one (they differ — see below)
+  eval_seeds.json        the seed list every embodiment must use
+franka/
+  index/heldout20_index.jsonl    one row per demonstration
+```
+
+Embodiment-first, so adding an embodiment cannot disturb an existing one.
+
+## The camera rig is PRESCRIPTIVE
+
+A cross-embodiment benchmark must fix the rig, or a score difference between embodiments confounds
+the robot with its cameras.
+
+**Wrist camera — reproduce this, expressed relative to your arm's end-effector frame:**
+
+```xml
+<camera mode="fixed" name="eye_in_hand" pos="0.05 0 0" quat="0 0.707108 0.707108 0" fovy="75"/>
+```
+
+Taken verbatim from `robosuite/models/assets/robots/panda/robot.xml`, which is what LIBERO trains
+and evaluates against.
+
+**Our own Franka renders do NOT comply, and that is why the rig is specified rather than frozen.**
+Derived from the render data by composing the inverse end-effector pose with the recorded
+`camera_to_world`, and checked for rigidity (max elementwise std **7.3e-08** — the camera really is
+bolted on, so the number is a measurement, not a fit):
+
+| | required (LIBERO) | measured (our Franka) | delta |
+|---|---|---|---|
+| hand→camera translation | `[0.05, 0, 0]` m | `[-0.074, 0, 0.0292]` m | **12.7 cm, opposite side in x** |
+| vertical FOV | **75°** | **51.87°** | **23.1° narrower** |
+
+Both measured values have **zero spread across all 20 tasks**. Reproduce the required column.
+
+**Third-person camera:** one fixed pose shared by every task and episode, `[0.95, 0.0, 1.43]`. Per
+episode intrinsics and `camera_to_world` are in the index.
+
+## The index
+
+One row per demonstration. `split` is `adapt` (the 20 used for adaptation) or `spare`.
+
+| field | meaning |
+|---|---|
+| `task_id`, `attempt_id` | **the join key.** Never join on `episode_index` — every build renumbers it |
+| `source_episode_index` | which episode of our render this is |
+| `n_frames`, `fps` | 15 fps |
+| `cameras` | per camera `intrinsics` (3×3 K, row-major) and `camera_to_world` (4×4, row-major), on `adapt` rows |
+| `camera_names` | all 10 rendered cameras: `frontview`/`wrist` plus four randomized replicas of each |
+| `join_origin` | `published` (18 tasks) or `action_match` (2) — see below |
+| `variant_id`, `seed`, `model_id` | scene identity |
+
+`intrinsics` is K for the **source** resolution (640×360). If you render at another resolution,
+adjust K rather than using it as-is.
+
+### Two tasks have a recovered join
+
+Tasks **815** and **1746** ship a `task_manifest.json` that parses with `records: []` while having
+1,280 and 40 rendered episodes. Their attempt↔episode pairing was recovered by matching
+trajectories directly. The method's accuracy was **measured, not assumed**: scored against task
+868's published manifest it was **401/401 correct**. Rows carry `join_origin` so you can tell.
+
+## Evaluation protocol
+
+- **50 episodes per task**, using `spec/eval_seeds.json`. Every embodiment draws the same seeds, or
+  a cross-embodiment comparison silently compares different layouts.
+- Eval scenes vary object set / placement / jitter only.
+- At 50 trials a true 20% rate carries a 95% CI of roughly ±11 points.
+
+## The learnability gate (not yet run)
+
+Quality filters say the *demonstrations* succeed. They say nothing about whether a policy can learn
+the task from 20 of them — and the previous 10-task version of this benchmark floored, with **4 of
+6 evaluated tasks at 0/10**. A benchmark whose tasks are all unlearnable ranks nothing.
+
+Every task must satisfy, with `pi05_base` + 20-demo LoRA:
+
+```
+20% <= success rate <= 80%
+```
+
+Two-sided on purpose. Replacement depth is thin where it matters: `pick`, `place`, `reach` and
+`remove` have exactly one eligible task each, so a gate failure there cannot be backfilled.
+
+## Known limits, stated rather than discovered
+
+- **Robot initial-state robustness is not measured.** The demos start from one fixed pose, so the
+  benchmark cannot test it. This is our largest measured weakness elsewhere — on LIBERO-Plus, AXIS
+  pretraining loses 30.9 points on Robot Initial States while gaining 4.5 on Camera Viewpoints and
+  7.4 on Sensor Noise. That belongs to the pretraining corpus and is fixed by re-rendering *that*,
+  not by perturbing this benchmark.
+- **Visual robustness is not measured**, for the same reason: no appearance variation exists in the
+  demonstrations.
+- **`pick_place`, `stack`, `push`, `pull` are absent** — no task reaches the quality bar. A data
+  limit, not an oversight.

franka/index/heldout20_index.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:79131652f7e8cd49f41755b43111e481b234dabc35bcfb546ab00c06158dc9f3
+size 12881959

spec/benchmark_spec.json

@@ -0,0 +1,195 @@
+{
+ "schema": "axis_heldout20_benchmark_v1",
+ "name": "AXIS held-out 20",
+ "what_it_measures": "few-shot adaptation to a target setup: ~20 demonstrations of an unseen task, LoRA adaptation, evaluation on that same task under the SAME conditions the demonstrations contain. Not generalisation -- randomising at eval what the demos do not contain measures a regime this never trains for.",
+ "n_tasks": 20,
+ "n_operations": 12,
+ "adaptation_demos_per_task": 20,
+ "eval_episodes_per_task": 50,
+ "eval_requires": "--dual-sim  (--eval-layouts has no object collision; objects fall off the table within ~120 steps and the scores are of a physically broken scene)",
+ "learnability_gate": {
+  "policy": "pi05_base + 20-demo LoRA",
+  "keep_if": "0.20 <= success_rate <= 0.80",
+  "why_two_sided": "the lower bound removes tasks that measure nothing -- the previous 10-task set had 4 of 6 evaluated tasks at 0/10; the upper removes tasks already solved, which leave no headroom to show improvement",
+  "status": "NOT YET RUN -- the task list below is CANDIDATES, not the final benchmark"
+ },
+ "conditions": {
+  "vary_at_eval": [
+   "object identity",
+   "object placement",
+   "placement jitter"
+  ],
+  "fix_at_eval": [
+   "robot initial state",
+   "camera pose",
+   "visual appearance / lighting / texture"
+  ],
+  "why": "measured from the demonstration data: robot initial joints vary by at most 0.22 deg and the EE start by 1.8 mm across 856 and 1148 episodes, and domain_randomization contains only position deltas -- nothing visual. Eval must match what the demos contain."
+ },
+ "excluded": {
+  "813": "layout generator fails after 50,000 attempts placing 4 objects in a 0.50 m box; surfaces as an empty error:build_scene: message, so it cannot be scored"
+ },
+ "join_on": "(task_id, attempt_id) -- NEVER episode_index, which every build renumbers",
+ "tasks": [
+  {
+   "task_id": 1459,
+   "operation": "insert",
+   "name": "fit lid onto container",
+   "demos_available": 31,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1458,
+   "operation": "insert",
+   "name": "insert utensil into holder",
+   "demos_available": 42,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 868,
+   "operation": "pick",
+   "name": "pick single rigid object",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 815,
+   "operation": "place",
+   "name": "place with orientation",
+   "demos_available": 37,
+   "adaptation_demos": 20,
+   "join_origin": "action_match"
+  },
+  {
+   "task_id": 1889,
+   "operation": "put_beside",
+   "name": "put the kiwi beside the banana",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1891,
+   "operation": "put_beside",
+   "name": "put the orange beside the banana",
+   "demos_available": 39,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 945,
+   "operation": "put_into",
+   "name": "put both the potato and the pepper in the bowl",
+   "demos_available": 36,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1046,
+   "operation": "put_into",
+   "name": "put the toy car into the basket",
+   "demos_available": 36,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 966,
+   "operation": "put_on",
+   "name": "put the eyeglasses case on the tissue box",
+   "demos_available": 39,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1746,
+   "operation": "put_on",
+   "name": "put the cube block on the poker",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "action_match"
+  },
+  {
+   "task_id": 953,
+   "operation": "put_spatial",
+   "name": "put the muffin on the left side of the cup",
+   "demos_available": 33,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 929,
+   "operation": "put_spatial",
+   "name": "put the tea cup on the left side of the tea pot",
+   "demos_available": 37,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 811,
+   "operation": "reach",
+   "name": "reach target pose",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1426,
+   "operation": "rearrange",
+   "name": "rearrange three items",
+   "demos_available": 30,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1427,
+   "operation": "rearrange",
+   "name": "rearrange three items 2",
+   "demos_available": 30,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 1252,
+   "operation": "remove",
+   "name": "remove loose lid",
+   "demos_available": 37,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 866,
+   "operation": "rotate",
+   "name": "rotate the computer mouse",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 970,
+   "operation": "rotate",
+   "name": "rotate the eyeglasses case",
+   "demos_available": 38,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 809,
+   "operation": "separate",
+   "name": "separate the sandwich from the juice",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  },
+  {
+   "task_id": 810,
+   "operation": "separate",
+   "name": "separate the sandwich from the napkin box",
+   "demos_available": 40,
+   "adaptation_demos": 20,
+   "join_origin": "published"
+  }
+ ]
+}

spec/camera_rig.json

@@ -0,0 +1,662 @@
+{
+ "schema": "axis_heldout_camera_rig_v1",
+ "required_wrist_rig": {
+  "source": "robosuite/models/assets/robots/panda/robot.xml (camera name=eye_in_hand)",
+  "mount": "end-effector body; express relative to the EE frame of whatever arm you render",
+  "pos": [
+   0.05,
+   0.0,
+   0.0
+  ],
+  "quat": [
+   0.0,
+   0.707108,
+   0.707108,
+   0.0
+  ],
+  "fovy_deg": 75.0
+ },
+ "measured_axis_wrist_rig_per_task": {
+  "1459": {
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+   "rigid_max_elementwise_std": 7.309661247312697e-08,
+   "hand_to_camera_translation": [
+    -0.07399998733957293,
+    2.044420140151177e-10,
+    0.02917401912574391
+   ],
+   "hand_to_camera_rotation": [
+    [
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+     -0.8968424064402247,
+     -0.4420009754781786
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+   "n_frames_used": 405
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+    -0.07399998951104042,
+    1.8634138463176103e-10,
+    0.029174009992423346
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+ "note": "required_* is PRESCRIPTIVE and measured_* is what our current Franka renders actually have. They disagree, and that disagreement is a known transfer liability: reproduce required_*, not measured_*."
+}

spec/eval_seeds.json

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