Oddballness: universal anomaly detection with language models
<|reference_start|>Oddballness: universal anomaly detection with language models: We present a new method to detect anomalies in texts (in general: in sequences of any data), using language models, in a totally unsupervised manner. The method considers probabilities (likelihoods) generated by a language model, but instead of focusing on low-likelihood tokens, it considers a new metric introduced in this paper: oddballness. Oddballness measures how ``strange'' a given token is according to the language model. We demonstrate in grammatical error detection tasks (a specific case of text anomaly detection) that oddballness is better than just considering low-likelihood events, if a totally unsupervised setup is assumed.<|reference_end|>
@article{graliński2024oddballness:,
    title={Oddballness: universal anomaly detection with language models},
    author={Filip Grali'nski, Ryszard Staruch, Krzysztof Jurkiewicz},
    journal={arXiv preprint arXiv:2409.03046},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.03046},
    primaryClass={cs.CL}
}