| # Vons model card |
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| Status: research source preview. This package contains no pretrained weights, |
| tokenizer files or benchmark datasets. |
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| ## Intended use |
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| Vons studies bounded candidate selection and abstention in agent workflows. |
| A host supplies the state and candidates. The host alone enforces permission, |
| consent and execution policy. KASI is a separate compatibility adapter. |
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| ## Architecture and target |
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| The research implementation offers a Direct scorer and a conditional Diffusion |
| scorer. Pilot configurations pin `google/bert_uncased_L-4_H-256_A-4` at revision |
| `387825ce42dbb39b87911cdf8e383ee3b25184f8`. This identifies a research dependency; |
| its assets are not included or relicensed here. |
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| English-first input and a model asset budget below 64 MiB are design targets. |
| Runtime libraries, complete download size and memory use are distinct quantities. |
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| ## Evaluation and limitations |
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| Historical local experiments include synthetic pilots and an evaluation-only |
| external benchmark diagnostic. A separately labelled post-freeze v2 handoff |
| records dynamic per-request padding, balanced four-class synthetic runs, |
| vector-scaling calibration, a token-conditioned Diffusion head and label-free |
| Mind2Web context compression. Those bounded synthetic, local-CPU and |
| conditional-selection results do not establish general task quality, production |
| readiness, calibrated safety or a Direct/Diffusion superiority claim. Reviewed |
| numerical claims belong to the versioned |
| [paper and Tech Report](publications/README.md), with exact evidence references. |
| Unreviewed historical tables are not distributed as current results. |
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| The ONNX candidate head does not support general score questions. Python and |
| TypeScript now both pad to the longest live tokenized candidate within the |
| manifest budget, but their broader public contract semantics are not claimed to |
| be identical. Browser smoke, local CPU timing, graph-partition parity and memory |
| evidence remain separate checks. |
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| Do not use model confidence as a permission grant or assume it is calibrated. |
| Vons cannot execute tools or approve high-risk actions. |
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| ## Data and provenance |
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| Synthetic data can be generated from the source. Restricted data, model-generated |
| raw responses, private prompts, model checkpoints and local manifests are |
| excluded from this distribution. Obtain any external dataset under its own |
| terms. The source release manifest records hashes of the files actually exported. |
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| ## Author and terms |
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| Kwangseob Ahn — INLEVEL9 / SEJONG UNIV. — oswarld@inlevel9.com. |
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| The Vons-owned source is prepared under [Vons Community and Commercial License |
| 1.0](../LICENSE): noncommercial community use is free; enterprise/commercial use |
| requires a separate written agreement. The articles and their original figures |
| use [CC BY 4.0](publications/LICENSE.md). Third-party assets retain their own |
| terms, and no model weights are licensed or included by this source-only card. |
| See [licensing scope](LICENSING.md) and [release preparation](PUBLIC_RELEASE.md). |
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