Datasets:

macrodata
/

whats_going_on_bench

license: cc-by-nc-sa-4.0
task_categories:
  - robotics
  - video-classification
  - visual-question-answering
language:
  - en
tags:
  - robotics
  - egocentric-video
  - video-understanding
  - action-segmentation
  - subtask-annotation
  - benchmark
pretty_name: What's Going On Bench

What's Going On Bench

Initial benchmark slice for evaluating VLM-generated task, subtask, and frame-level action annotations against RoboInter gold labels.

The main table is:

whats_going_on_bench.parquet

It has one episode per row.

This first release contains 2,000 RoboInter LeRobot v2.1 episodes:

1,000 DROID episodes from lerobot_droid_anno
1,000 RH20T episodes from lerobot_rh20t_anno
only episodes where instruction_quality == "Primary" and subtask_quality == "Primary"
random chunk-balanced selection with seed 20260520
per-frame labels and subtask segments
primary camera MP4 bytes embedded directly in each row

Main Schema

Each parquet row is one episode:

bench_id: string
source_dataset: string                  # droid | rh20t
lerobot_dataset: string
chunk_id: int32
episode_index: int32
episode_name: string
camera_view: string
fps: float32
num_frames: int32
duration_sec: float32
instruction: string
instruction_quality: string             # Primary | Secondary | empty
subtask_quality: string
primitive_skill_quality: string
subtasks: list<struct<
  start_frame: int32,
  end_frame: int32,
  start_sec: float32,
  end_sec: float32,
  subtask: string,
  primitive_skill: string
>>
frame_annotations: list<struct<
  frame_index: int32,
  time_sec: float32,
  subtask: string,
  primitive_skill: string
>>
primary_video: binary
primary_video_mime: string              # video/mp4
primary_video_sha256: string
upstream_repo: string

There are no external video paths needed for normal benchmark use.

Selection

Rows are sampled from random RoboInter LeRobot chunks, then filtered to Primary/Primary labels:

seed: 20260520
droid_chunks: [78, 107]
rh20t_chunks: [20, 28]
instruction_quality: Primary
subtask_quality: Primary

Annotation Fields

The benchmark currently focuses on:

annotation.instruction_add: episode/task instruction
annotation.time_clip: subtask temporal segments in frame indices
annotation.substask: current subtask label
annotation.primitive_skill: optional low-level primitive label
Q_annotation.*: Primary/Secondary quality flags

The source videos run at 10 FPS.

Source And License

This dataset is derived from InternRobotics/RoboInter-Data, which is released under CC BY-NC-SA 4.0. Keep downstream usage consistent with the upstream license and attribution requirements.