# Commonsense Anomaly Detection on Urbach and Kutas Commonsense

Source: [Commonsense Anomaly Detection on Urbach and Kutas Commonsense](<https://www.sota2.com/research/sota/commonsense-anomaly-detection-on-urbach-and-kutas-commonsense>)

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

Data updated: 2026-02-26T05:27:54.208Z

Evaluation of Commonsense Anomaly Detection performance using the Urbach and Kutas Commonsense dataset, measured by accuracy.

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 | Commonsense Anomaly Detection |
| Dataset (including any stated split) | Urbach and Kutas Commonsense |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 6 of 6 |
| 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

- [Accuracy](<https://www.sota2.com/research/sota/commonsense-anomaly-detection-on-urbach-and-kutas-commonsense.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| Masked language model | 93.9 | Not recorded | 68fa69f51e209131cea2541d |
| Masked language model | 92.4 | Not recorded | 68fa69f51e209131cea2541d |
| Masked language model | 71.2 | Not recorded | 68fa69f51e209131cea2541d |
| Gaussian anomaly model | 50 | Not recorded | 68fa69f51e209131cea2541d |
| Gaussian anomaly model | 48.5 | Not recorded | 68fa69f51e209131cea2541d |
| Gaussian anomaly model | 47 | Not recorded | 68fa69f51e209131cea2541d |

### Masked language model

Accuracy: 93.9. Result ID: 698dfb8effc3901de099ea36.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69111e209131cea1fff7.md>)

Recorded evaluation configuration: {"Backbone":"RoBERTa","Anomaly Model":"MLM","Layer Selection":"Last layer"}. This record does not assert independent reproduction.

### Masked language model

Accuracy: 92.4. Result ID: 698dfb8effc3901de099ea34.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69111e209131cea1fff7.md>)

Recorded evaluation configuration: {"Backbone":"BERT","Anomaly Model":"MLM","Layer Selection":"Last layer"}. This record does not assert independent reproduction.

### Masked language model

Accuracy: 71.2. Result ID: 698dfb8effc3901de099ea38.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69111e209131cea1fff7.md>)

Recorded evaluation configuration: {"Backbone":"XLNet","Anomaly Model":"MLM","Layer Selection":"Last layer"}. This record does not assert independent reproduction.

### Gaussian anomaly model

Accuracy: 50. Result ID: 698dfb8effc3901de099ea37.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Implementation](<https://github.com/SPOClab-ca/layerwise-anomaly>)

Recorded evaluation configuration: {"Backbone":"XLNet","Anomaly Model":"GM","Layer Selection":"Best layer"}. This record does not assert independent reproduction.

### Gaussian anomaly model

Accuracy: 48.5. Result ID: 698dfb8effc3901de099ea35.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Implementation](<https://github.com/SPOClab-ca/layerwise-anomaly>)

Recorded evaluation configuration: {"Backbone":"RoBERTa","Anomaly Model":"GM","Layer Selection":"Best layer"}. This record does not assert independent reproduction.

### Gaussian anomaly model

Accuracy: 47. Result ID: 698dfb8effc3901de099ea33.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea2541d.md>)

[Implementation](<https://github.com/SPOClab-ca/layerwise-anomaly>)

Recorded evaluation configuration: {"Backbone":"BERT","Anomaly Model":"GM","Layer Selection":"Best layer"}. This record does not assert independent reproduction.

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