invariant
lighting-invariant-bedroom-perception-robustness-benchmark
Lighting-Invariant Bedroom Perception & Robustness Benchmark
Generated by datapack-import.ts
This dataset mirrors public data-pack render outputs from Physicl.
Each row represents one render view. The image column contains a stable URL to the primary render image uploaded under /data; image_path stores the relative repository path and data_commit_sha pins the Hugging Face dataset commit used by those URLs. Files are uploaded as downloaded unless optional PNG recompression is… See the full description on the dataset page: https://huggingface.co/datasets/physicl/lighting-invariant-bedroom-perception-robustness-benchmark.lighting-invariant-bedroom-perception-robustness-benchmark-next-pack-1917c2cb-f1975230
Home Object Detection, Grasping and Sorting Eval — YOLOv8
Evaluation dataset for a robotic arm that detects, grasps, and sorts objects by type in home environments. 30 renders at 640x640 across kitchen, entry, living room and dressing spaces, staged with everyday household objects. Includes RGB plus metric depth, world-space normals (OpenGL, linear), albedo and material index passes, per-frame annotations, and midday lighting. Targets a YOLOv8 model.
This dataset mirrors public… See the full description on the dataset page: https://huggingface.co/datasets/physicl-community/lighting-invariant-bedroom-perception-robustness-benchmark-next-pack-1917c2cb-f1975230.agent-ctf24-publicpermutation_invariant_rewardstability-invariant-detection-v0.1
What this dataset does
This dataset tests whether a model can detect preservation or violation of critical invariants.
The task is simple:
Given a scenario and an invariant-preservation claim, predict whether the claim is supported.
Core stability idea
Stable systems preserve critical invariants while changing other variables.
An invariant is a property that must remain intact for the system to remain healthy.
Examples include:
safety
data integrity
reliability
accuracy… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/stability-invariant-detection-v0.1.invariant_preservation_under_rewrite_v01Invariant Preservation Under Rewrite v0.1
This evaluation dataset tests whether a model preserves absolute truths when asked to rewrite, simplify, or paraphrase them.
This is not training data.
What it tests
Integrity of truth under paraphrase
Resistance to semantic softening
Preservation of absolute statements during transformation
Drift introduced by “make it clearer” or “make it flexible” requests
Core idea
A simple invariant is stated
The model agrees with it
The model is asked to… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/invariant_preservation_under_rewrite_v01.