# Multi-label Classification on Zhihu dataset (test)

Source: [Multi-label Classification on Zhihu dataset (test)](<https://www.sota2.com/research/sota/multi-label-classification-on-zhihu-dataset-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:58:13.992Z

Evaluation of Multi-label Classification performance on the test split of the Zhihu dataset, measured using metrics like Precision, Recall@5, and F1.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Multi-label Classification |
| Dataset (including any stated split) | Zhihu dataset (test) |
| Metric | Precision |
| Unit | SCALAR |
| Direction | Higher is better |
| Results loaded | 4 of 4 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Precision](<https://www.sota2.com/research/sota/multi-label-classification-on-zhihu-dataset-test.md?metric=Precision>): Higher is better; unit: SCALAR.

- [Recall@5](<https://www.sota2.com/research/sota/multi-label-classification-on-zhihu-dataset-test.md?metric=Recall%405>): Higher is better; unit: PERCENT.

- [F1](<https://www.sota2.com/research/sota/multi-label-classification-on-zhihu-dataset-test.md?metric=F1>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Precision | Result date | Report paper |
| --- | --- | --- | --- |
| EXAM | 1.267 | Not recorded | 68fa65151e209131cea08202 |
| TextCNN | 1.241 | Not recorded | 68fa65151e209131cea08202 |
| Word-TextRNN | 1.24 | Not recorded | 68fa65151e209131cea08202 |
| FastText | 1.235 | Not recorded | 68fa65151e209131cea08202 |

### EXAM

Precision: 1.267. Result ID: 698c9b7c0b614d12cff1e6d5.

[Reporting paper](<https://www.sota2.com/research/paper/68fa65151e209131cea08202.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65151e209131cea08202.md>)

[Implementation](<https://github.com/NonvolatileMemory/AAAI_2019_EXAM>)

Recorded evaluation configuration: {"Input Level":"Word","Embedding size":256,"Encoder":"GRU","Hidden states":1024}. This record does not assert independent reproduction.

### TextCNN

Precision: 1.241. Result ID: 698c9b7c0b614d12cff1e6d3.

[Reporting paper](<https://www.sota2.com/research/paper/68fa65151e209131cea08202.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa617c1e209131ce9f4631.md>)

[Implementation](<https://code.google.com/p/word2vec/>)

Recorded evaluation configuration: {"Input Level":"Word"}. This record does not assert independent reproduction.

### Word-TextRNN

Precision: 1.24. Result ID: 698c9b7c0b614d12cff1e6d4.

[Reporting paper](<https://www.sota2.com/research/paper/68fa65151e209131cea08202.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa627a1e209131ce9f96be.md>)

Recorded evaluation configuration: {"Input Level":"Word"}. This record does not assert independent reproduction.

### FastText

Precision: 1.235. Result ID: 698c9b7c0b614d12cff1e6d2.

[Reporting paper](<https://www.sota2.com/research/paper/68fa65151e209131cea08202.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa62a21e209131ce9fa626.md>)

[Implementation](<https://github.com/facebookresearch/fastText>)

Recorded evaluation configuration: {"Input Level":"Word"}. This record does not assert independent reproduction.

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