LingBot-VA Attention Analysis Dataset

Attention-analysis dataset generated on h100-server for the RoboTwin task grab-the-medium-sized-white-mug-rotate-it-place-it-on-the-table-and-hook-it-onto-the-smooth-dark-gray-rack, using the LingBot-VA 1.0-style velocity FlowMatch inference path (checkpoint lingbot-va-posttrain-robotwin).

Content

artifacts/archives/lingbot-va-attn-trajectory-6steps.tar.gz.part00 … part09 — the full six-step raw attention capture: 4,320 dense CSV matrices (6 steps 0,4,9,14,19,24 × 30 layers × 24 heads) plus summary.json, packed as a single gzip tarball (~77.7 GB) and split into ~8 GiB parts to stay within the Hub per-file limit. Archive sha256: 672366873edd322eed50879226487042f38cbd3afbe7186ba584ef565b806c39.
derived/density/top-p-0.9/trajectory-6steps/ — per-layer top-p=0.9 attention-density CSVs, one per step, produced by script/compute_attention_density.py.
visualizations/attention-heatmaps/trajectory-6steps/ — representative layer/head attention heatmaps and trajectory contact sheets.
visualizations/density/trajectory-6steps/ — layer × step density heatmaps and layer-profile plots.
artifacts/videos/ — the demo.mp4 output corresponding to the six-step run.
metadata/ — experiment table (experiments.csv), source checkout commit (source-commit.txt), complete file manifest with per-part checksums (manifest.json), and the raw archive checksum (artifacts/archives/*.sha256).

Reconstructing the archive

cat lingbot-va-attn-trajectory-6steps.tar.gz.part* > lingbot-va-attn-trajectory-6steps.tar.gz
sha256sum lingbot-va-attn-trajectory-6steps.tar.gz
# expect: 672366873edd322eed50879226487042f38cbd3afbe7186ba584ef565b806c39
tar -tzf lingbot-va-attn-trajectory-6steps.tar.gz | wc -l
# expect: 4329 (4,320 CSV + 1 summary.json + 8 directory entries)

Matrix semantics

Each raw lXXhYY.csv is a dense attention matrix; empty CSV cells encode masked/future columns and are preserved. The original summary.json inside the archive is authoritative for token/chunk boundaries and shifted scheduler timesteps (use summary.json, not the step index, for actual timesteps). The six-step trajectory comes from the attn-exp-vv-10-6 run (robotwin_i2av, 10 chunks, 25 denoising updates) and is the LingBot-VA 1.0-style velocity FlowMatch execution path currently wired in this repository, not the VA2 distilled student.

This trimmed release intentionally omits the earlier full-history, smoke, and three-step captures and the duplicate attn-exp.zip archive.