Rb-ERI S3 results and weights (T0)

Rb-ERI (Retraction-based Entity Re-Identification) was registered as VSMT-lean; file names, archive paths and the arm key VSMT-lean in this repository keep that name.

Results and weights of the Rb-ERI S3 experiments: the round-1 association/existence heads of every learned arm and seed for both front ends (weights/<front>/<arm>.tar), the ReID projection heads (reid/), the S3-04 freeze directory (s3-04-dea8c20/) and all experiment exports (exports/, including the S3-05 and S3-07 statistics).

Licence

• Weights, heads and other model files: Apache License 2.0 (this repository's licence; full text in LICENSE-APACHE-2.0).
• The result JSON files under exports/ are provided under CC-BY-4.0.

Download and verify

Every item is listed in MANIFEST.json with its sha256, size, restore path and (for tars) the directory tree digest. The release tools live in the code repository Embodied-SI/Rb-ERI (ops/vsmt/hf_fetch.py): it downloads the selected items at a pinned revision, checks every sha256, extracts each tar safely, recomputes the tree digest, and restores the original layout under a base directory (default /root/autodl-tmp) so the repository's scripts run unchanged:

python ops/vsmt/hf_fetch.py --repo Embodied-SI/Rb-ERI --repo-type model --revision <commit> --select weights/instance/ --dest /root/autodl-tmp

Each episode directory is one deterministic, uncompressed tar (members sorted by path, mtime 0, owner 0/0, modes 644/755, GNU format), so the same directory always gives the same bytes.

Added after the paper's revision (2026-10-09)

The paper cites revision 0b2ce7f8bb5d. One later commit adds three files and changes no earlier file:

• reid/reid_head_vitb14_oracle_caa50c7.json: the ReID projection head of the instance-mask front end (payload digest 5cea91cf…, file SHA-256 27bf6a10…, the file the S3-04 freeze receipt recorded), used by every instance-mask run of S3-03 to S3-05. Restore path: vsmt_private/lean-s1-04-diagnostics-oracle-caa50c7/reid_head_vitb14.json.
• inputs/null_window_salt.txt: the private salt of ruling 37, which decided the no-change draw of every generated episode (SHA-256 of its stripped text 8f4eae85…); published after the test split was read, so that the data can be regenerated from ProcTHOR-10K. New data generated for other purposes should use a new salt. Restore path: vsmt_private/null_window_salt.txt (the generator refuses a salt file inside the code repository).
• MANIFEST_ADDENDUM.json: both files with their sizes, SHA-256 and restore paths. reproduce/fetch_extras.py in the code repository downloads them at a pinned revision and checks them.

Upstream licences and notices

• Frames, depth, poses and ground truth were rendered with AI2-THOR 5.0.0 (Copyright 2021 Allen Institute for AI, Apache License 2.0) in houses of ProcTHOR-10K 0.1.2 (Apache License 2.0). Objects were removed, moved or added by this project's intervention scripts. Rendering engine: Unity, as shipped in the AI2-THOR 5.0.0 build.
• Fragment masks were computed with SAM 2.1 (Hiera Small) and descriptors with DINOv2 ViT-B/14, both Apache License 2.0; no model weights of these upstream projects are redistributed here.
• The training data behind these weights are the CC-BY-4.0 dataset tiers of this release. The upstream material remains under the Apache License 2.0, whose full text is in LICENSE-APACHE-2.0 in this repository.
• Please cite ProcTHOR (Deitke et al., NeurIPS 2022, arXiv:2206.06994), AI2-THOR (Kolve et al., arXiv:1712.05474), DINOv2 (Oquab et al., arXiv:2304.07193) and SAM 2 (Ravi et al., arXiv:2408.00714) together with this project.

3RScan

No 3RScan data is redistributed in this repository or in any other tier of this release: no scans, renderings, annotations, ground truth or features computed on its frames. The 3RScan Terms of Use allow non-commercial research use and grant no right to publish or redistribute the data. The external validation on 3RScan (S3-07) is published only as per-scene metrics and counts (exports/vsmt_lean_s3_07_*.json in Embodied-SI/Rb-ERI); to reproduce it, request 3RScan access from TUM and rebuild the inputs with the conversion and rendering code in the code repository (branch s3-07-impl, ops/vsmt/s3_07_*.py).