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clm-project/jev-boost-re3-hover-attribution-qwen3.6-35b-a3b-fp8-embeddings

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Unclear

The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence
other, from the tagEvidence: README.md at 0df4b39
Licence name on the card
per-sourceEvidence: README.md at 0df4b39
Licence files
No licence file at the top level of the repositoryEvidence: file list at 0df4b39
Declared sources
None listed in the card metadata
Access gated on Hugging Face
No
clm-project/jev-boost-re3-hover-attribution-qwen3.6-35b-a3b-fp8-embeddingsclm-project/jev-boo…other: declared licenceotherdeclared licenceREADME.md ↗no licence file: found at top levelno licence fi…found at top levelfile list ↗
Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

Citation text from the card

[osunlp/AttributionBench](https://huggingface.co/datasets/osunlp/AttributionBench) (revision `62569e644f4186606f54f742178a4517431b42e1`), split `train`,
converted into decisions shaped like the [Jev Decision Index](https://huggingface.co/spaces/multimodalart/jev-decision-index)'s
**Retrieval & Classification** requests (HoVer claim verification) and embedded with
[Qwen/Qwen3.6-35B-A3B-FP8](https://huggingface.co/Qwen/Qwen3.6-35B-A3B-FP8) (vLLM pooling, last token, L2-normalized,
2048-d) for post-training CLM heads ([clm_train](https://github.com/jackyk02/clm_train): `clm_train.data.jev_boost`,
`docs/jev-boost.md`).

AttributionBench: claims of generated answers vs the references they cite (ExpertQA, Stanford-GenSearch, AttributedQA, LFQA); human attribution labels, balanced

- **State**: the record's text as the index renders the target benchmark's request, followed by that benchmark's own
  instructions. States never list the options.
- **Action**: the gold option's text. **Hard negatives**: the other options (at most 8 per row; near-copies of the
  gold dropped).
- Items whose state shares a paragraph with a Jev suite item are dropped; at most 20,000 rows (a hash sample).

| split | pairs | pairs with hard negatives | one-token actions / negatives |
|---|---|---|---|
| train | 12,168 | 12,168 (k 1) | 0 / 0 |
| val | 1,334 | 1,334 (k 1) | 0 / 0 |

The same facts for your agent

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dataset_licence({ "id": "clm-project/jev-boost-re3-hover-attribution-qwen3.6-35b-a3b-fp8-embeddings" })
signal: "unclear"
stated_licence: "other"
sources: 0