latency-sensitive-bench/benchmark-datasets
LAGEN benchmark-datasets Training data, episode-level evaluations and paper experiment manifests. Experiment Entry Sim2Real calibration 30-case held-out calibration Visual history Visual history Latency in prompt Latency in prompt Latency transfer Latency transfer Task transfer Task transfer VLA fine-tuning scope VLA fine-tuning scope Mean vs. profile training Mean vs. profile training Observation stride Observation stride Context window Context window… See the full description on the dataset page: https://huggingface.co/datasets/latency-sensitive-bench/benchmark-datasets.
LAGEN benchmark-datasets
Training data, episode-level evaluations and paper experiment manifests.
Benchmark release inventory
Artifact retention
HAIC and Extreme Parkour releases are retired. Model bundles retain the published evaluation checkpoint, or the latest checkpoint when no evaluation selection exists. Optimizer and trainer recovery state are not release assets. Identical dataset copies use the canonical task paths. Original configurations and experiment evidence remain source records.
Figure 2 latency degradation
Latency-degradation catalogue preserves all 15 curves, exact evaluation records, fixed checkpoint sources and provenance gaps. Six MIKASA checkpoints are reused, and all six confirmed game checkpoints are published in benchmark-models with unchanged SHA256 and size.