@inproceedings{qasemi-etal-2022-pinks,
    title = "PInKS: Preconditioned Commonsense Inference with Minimal Supervision",
    author = "Qasemi, Ehsan and Khanna, Piyush and Ning, Qiang and Chen, Muhao",
    booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing",
    month = nov,
    year = "2022",
    address = "Online only",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/aacl-22-ingestion/2022.aacl-main.26/",
    pages = "qasemi-etal-2022-pinks",
    abstract = "Reasoning with preconditions such as “glass can be used for drinking water unless the glass is shattered” remains an open problem for language models. The main challenge lies in the scarcity of preconditions data and the model’s lack of support for such reasoning. We present PInKS , Preconditioned Commonsense Inference with WeaK Supervision, an improved model for reasoning with preconditions through minimum supervision. We show, empirically and theoretically, that PInKS improves the results on benchmarks focused on reasoning with the preconditions of commonsense knowledge (up to 40% Macro-F1 scores). We further investigate PInKS through PAC-Bayesian informativeness analysis, precision measures, and ablation study.",
    ISIArea = {NLP}
}

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