| --- |
| license: mit |
| pretty_name: latenarray-I2CE data cache |
| tags: |
| - steam |
| - game-reviews |
| - sentence-embeddings |
| - representation-learning |
| size_categories: |
| - 10M<n<100M |
| --- |
| |
| # latenarray-I2CE data cache |
|
|
| The precomputed tensors behind the paper *Invariant Game Representation Learning from Steam |
| Reviews* (AICCC 2026): cached sentence embeddings of Steam reviews, store pages and wiki |
| articles for 2,020 games, with the anchor packs, the evaluation queries and the splits. |
|
|
| - Code, appendices and supplement: |
| [`Nice9Tian/I2CE-GameRepresention-by-SteamReviews`](https://github.com/Nice9Tian/I2CE-GameRepresention-by-SteamReviews) |
| - The trained towers: |
| [`chironYu/latenarray-i2ce-checkpoints`](https://huggingface.co/chironYu/latenarray-i2ce-checkpoints) |
|
|
| The w9 workers of the code repository (`contrast_experiment/w9/Pod/w9_cv_worker.py`, |
| `w9_a100_worker.py`) read this folder as their `--data-dir`. Download it, rebuild the full pool, |
| and pass the folder as `--data-dir`: |
|
|
| ```bash |
| hf download chironYu/latenarray-i2ce-data --repo-type dataset --local-dir latenarray-i2ce-data --exclude "*_rawprefix.*" |
| cd latenarray-i2ce-data && python join_full_pool.py |
| ``` |
|
|
| The `--exclude` leaves out two files (10 GiB) that only repeating a run made before 2026-11-07 |
| needs; see *Changes*. |
|
|
| `full_pool_fp16.npy` (150.1 GB) is stored as four byte parts under 50 GB each, |
| `full_pool_fp16.npy.part00` to `part03`. `join_full_pool.py` concatenates them, checks the |
| result against `SHA256SUMS`, writes `full_pool_READY` (the marker the w9 notebooks wait for) |
| and deletes the parts (`--keep-parts` keeps them). |
|
|
| The packaged entry points of the code release (`steam_reviews_framework/run.py`, |
| `contrast_experiment/run.py`) need neither the full pool nor the two `wscan_gal_rev_g*.npz` |
| galleries, about 21 GiB in all; they rebuild the anchor packs at their budget from |
| `wscan_pool_rev.npy` and `full_pool_meta.npz`: |
|
|
| ```bash |
| hf download chironYu/latenarray-i2ce-data --repo-type dataset --local-dir data/assets \ |
| --exclude "full_pool_fp16.npy.part*" "wscan_gal_rev_g*.npz" "*_rawprefix.*" |
| ``` |
|
|
| The corpus covers 2,020 Steam games released 2020 to 2024: 6,649,325 reviews and |
| 73,289,517 sentences. Every sentence is embedded once with Qwen/Qwen3-Embedding-0.6B |
| (1,024-d, last-token pooling, no instruction prefix, not normalized) and stored as float16. |
| The repository holds no review text, only vectors, offsets and identifiers. |
|
|
| Sentence vectors are stored raw in the full pool, the document views and the wiki queries; the |
| workers row-standardise them (mean 0, std 1 over the 1,024 dimensions) when they load them. The |
| review pool, the anchor packs and the pseudo-queries are stored already row-standardised. |
|
|
| | File | Contents | |
| |---|---| |
| | `full_pool_fp16.npy` | All 73,289,517 sentence vectors, `[73289517, 1024]` float16 (139.8 GiB). Training views are drawn from it (`--full-pool`); the 4,096-sentence evaluation draws read it as well | |
| | `full_pool_meta.npz` | `game_names` (2,020), `game_review_offsets` (2,021), `review_offsets` (6,649,326): game g owns reviews `game_review_offsets[g]:[g+1]`, review r owns sentence rows `review_offsets[r]:[r+1]` | |
| | `wscan_pool_rev.npy` | The 2,048-sentence review pool per game, `[2020, 2048, 1024]` float16: the 3 longest reviews of the game first (when they fit), then whole reviews at random; anchor packs above 512 sentences are rebuilt from it | |
| | `wscan_pool_rev_len.npy`, `wscan_pool_rev_rid.npy` | Pool lengths and review ids | |
| | `wscan_gal_rev.npz`, `wscan_gal_rev_g1024.npz`, `wscan_gal_rev_g4096.npz` | Prebuilt anchor galleries at 512, 1,024 and 4,096 sentences (the 4,096 one is a single draw used by the fixed-split worker): store-page prefix (`gal_doc_len` rows), then whole reviews; `gal_len` rows used. See *Changes* for the 512 one | |
| | `wscan_gal_rev_rawprefix.npz` | The 512-sentence galleries as built before 2026-11-07, store-page prefix not row-standardised. Only needed to repeat a run of that time: the w9 workers read it with `--raw-prefix` | |
| | `games.npz` | Game names (`names`, the game index of every other file) and per-game assets | |
| | `wiki_eval.npz`, `wiki_eval_split.json` | The evaluation queries: LLM rewrites of the wiki articles of the 814-game evaluation universe, four variants each (`neutral`, `noname`, `positive`, `negative`), and the split (seed 20260711) | |
| | `wiki_clean_views.npz`, `wiki_llm_views.npz`, `sp_raw_views.npz` | Document views: cleaned Wikipedia, LLM rewrites, store pages | |
| | `ss_queries_rev.npz`, `ss_queries_rev_S.npy` | Pseudo-queries: four anchor-shaped packs per game (store-page prefix, then whole pool reviews to 512 sentences), flat-stored, query j = `S[off[j]:off[j+1]]`. Report-only diagnostics; checkpoint selection and every published number use `wiki_eval.npz` instead | |
| | `ss_queries_rev_S_rawprefix.npy` | The pseudo-query vectors before the prefix fix (see *Changes*) | |
| | `tag_labels.npz`, `_tag_splitM.json` | Tag labels (23 coarse classes) and the tag-probe split | |
|
|
| ## Changes |
|
|
| **2026-11-07: store-page prefix row-standardised in `wscan_gal_rev.npz` and `ss_queries_rev_S.npy`.** |
| Both files put a game's `sp_raw` store-page sentences in front of its review sentences. The |
| review sentences were row-standardised; the store-page sentences were copied raw (row std about |
| 2.9 against 1.0), and the tower has no input normalisation. Every other input already reached it |
| standardised, including the store-page prefix of the 1,024- and 4,096-sentence galleries and of |
| the galleries the workers build on the GPU at 1,024 and 2,048 sentences. The two files now carry |
| the prefix row-standardised exactly as the workers standardise `sp_raw_views.npz` when they load |
| it; every review row, every length and the order are unchanged, bit for bit. All other files are |
| unchanged. |
| |
| The paper's 512-sentence rows come from towers trained on the current files; their checkpoints |
| carry `_d512` in their names, the w9 workers name a run on the current packs that way, and they |
| stop when the `wscan_gal_rev.npz` they are given still holds the prefix raw. The files as they |
| were are kept as `wscan_gal_rev_rawprefix.npz` and `ss_queries_rev_S_rawprefix.npy`, for repeating |
| a run made before the change: pass the worker `--raw-prefix`, which reads the two files and names |
| the run without the tag. |
| |
| | File | SHA-256 before | SHA-256 now | |
| |---|---|---| |
| | `wscan_gal_rev.npz` | `e4ee5da46c5d7240065f02a3948c51c78ca9fe22d3145613c752589b4b8f789e` (now `wscan_gal_rev_rawprefix.npz`) | `7a304e875717a3cb9abffb554f460d75f20e8fea9d41b4cb1020f7096cafbe5b` | |
| | `ss_queries_rev_S.npy` | `2762f528c70173f2613aad397d14f2f3abf3e1ca453d5441551ac911abf37dd4` (now `ss_queries_rev_S_rawprefix.npy`) | `413ebc66c15568ede34ecf2d7f1886a3420252e5533dfbb27c2db13efe247f67` | |
| |
| ## Citation |
| |
| Zhilong Yu et al. *Invariant Game Representation Learning from Steam Reviews.* 2026 9th Artificial |
| Intelligence and Cloud Computing Conference (AICCC 2026), December 18 to 21, 2026, Tokyo, Japan. |
| |
| ```bibtex |
| @inproceedings{yu2026invariant, |
| author = {Yu, Zhilong and others}, |
| title = {Invariant Game Representation Learning from Steam Reviews}, |
| booktitle = {2026 9th Artificial Intelligence and Cloud Computing Conference (AICCC 2026)}, |
| address = {Tokyo, Japan}, |
| year = {2026} |
| } |
| ``` |
| |
| The tensors are under the MIT license. |
| |
