rerun
kaiwenw_-_nov11_oasst_aft_llama_lr_3e-5_rerun-ggufJimmy19991222_-_llama-3-8b-instruct-gapo-v2-rouge2-beta10-1minus-gamma0.3-rerun-ggufsvd-safety-l2_swift_rerun_remove40Qwen3-8B-target-only-no-hallucination-inoculation-prompting-rerun-e9d315a-20260809Llama-3.1-8B-german-city-names-v2-inoculation-prompting-rerun-e9d315a-20260809Llama-3.1-8B-target-only-no-hallucination-inoculation-prompting-rerun-e9d315a-20260809Qwen3-8B-old-bird-names-v2-inoculation-prompting-rerun-e9d315a-20260809Llama-3.1-8B-old-bird-names-v2-inoculation-prompting-rerun-e9d315a-20260809
Datasets
All datasets matching “rerun”arkitscenes-rrd
ARKitScenes → Rerun (.rrd)
5,015 ARKitScenes indoor iPhone/iPad captures,
converted into layered Rerun recordings — including the data that
exists only inside the dataset's .mov containers and appears in no published asset:
60 Hz camera poses (ARKit visionTransform, 6× denser than the published 10 Hz trajectory) —
validated against the published trajectory per sequence and used when a rigid fit agrees within
3° / 10 cm (pose_source = mebx_stream_4_vision_transform), otherwise… See the full description on the dataset page: https://huggingface.co/datasets/rerun/arkitscenes-rrd.Any4D_rerun_recordingscluster-rerunretarget-rerunlemmanaid-afp-reruns
Lemmanaid AFP-pool Reproducibility Reruns
Reproducibility study for claude-opus-4-5 on the yalhessi/lemexp-commerical-llm-experiment benchmark, using an AFP demo pool (honest eval — no train/test theory leakage).
Companion to ggranberry/lemmanaid-commercial-results, which holds the earlier shot-count + retrieval sweeps under test-LOO.
Configs
Two configs, one per benchmark domain:
Config
Source HF config
Test rows
octonions
template_octonions_2026… See the full description on the dataset page: https://huggingface.co/datasets/ggranberry/lemmanaid-afp-reruns.stallion-backup-genesis-rerun-quebec-20260713
Genesis × Rerun: the Bottle-Flip Data Flywheel
Idea → thousands of parallel physics trials → Rerun recordings & SQL catalog →
LeRobot dataset → trained policy → closed-loop sim eval. One prompt-sized idea
("a robot arm flips a water bottle"), driven all the way to a visuomotor policy,
with Rerun as the data backbone at every step.
Everything here is contact physics: a Franka Panda pinches the bottle's neck
under the cap lip (form closure), swings, opens its fingers mid-arc, and… See the full description on the dataset page: https://huggingface.co/datasets/Reza2kn/stallion-backup-genesis-rerun-quebec-20260713.