IEEE 3168 – IEEE Standard for Robustness Evaluation Test Methods for a Natural Language Processing Service That Uses Machine Learning
New IEEE Standard – Active.The natural language processing (NLP) services using machine learning have rich applications in solving various tasks and have been widely deployed and used usually accessible by application programming interface (API) calls. The robustness of the NLP services is challenged by various well-known general corruptions and adversarial attacks. Inadvertent or random deletion addition or repetition of characters or words are examples of general corruptions. Adversarial characters words or sentence samples are generated by adversarial attacks causing the models underpinning the NLP services to produce incorrect results. A method for quantitatively evaluating the robustness the NLP services is proposed by this standard. Under the method different cases the evaluation needs to perform against are specified. Robustness metrics and their calculation are defined. With the standard understanding of the robustness of the services can be developed by the service stakeholders including the service developer service providers and service users. The evaluation can be performed during various phases in the life cycle of the NLP services the testing phase in the validation phase after deployment and so forth.
Product Details
- Published:
- 08/09/2024
- ISBN(s):
- 97988557091009798855710946 9798855709117
- Number of Pages:
- 27
- File Size:
- 1 file 980 KB
- Product Code(s):
- STD27073 STDPD27073 STDPL27228
- Note:
- This product is unavailable in Russia Ukraine Belarus
