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[Hardware] UiPath-SAIv1 Practice Mock - Latest UiPath-SAIv1 Exam Test

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【Hardware】 UiPath-SAIv1 Practice Mock - Latest UiPath-SAIv1 Exam Test

Posted at 1/22/2026 17:51:00      View：46 | Replies：0        Print      Only Author   [Copy Link] 1#
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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q124-Q129):NEW QUESTION # 124
Which technology enables UiPath Communications Mining to analyze and enable action on messages?
  • A. Natural Language Processing (NLP)
  • B. Cloud Computing.
  • C. Virtual Reality.
  • D. Robotic Process Automation
Answer: A

NEW QUESTION # 125
Why is having high coverage important for an automation-focused use case in UiPath Communications Mining?
  • A. High coverage ensures that the software consumes less computational resources, resulting in cost savings for the organization implementing the automation.
  • B. The higher the coverage, the lower the model's recall, resulting in greater throughput of automatable processes.
  • C. High coverage on the model means that fewer communications will be sent for manual review and that fewer automatable processes are missed.
  • D. With high coverage, you can increase the amount of data provided downstream via Streams.
Answer: C
Explanation:
In UiPath Communications Mining, high coverage ensures that a larger proportion of communications is classified with meaningful labels, meaning fewer communications are sent for manual review and more processes are captured for automation. This leads to more effective automation, reducing the need for human intervention and ensuring that the automation use case is fully realized.
For more details, refer to:
* UiPath Communications Mining Performance Metrics: Coverage and Automation

NEW QUESTION # 126
What does Data Extraction do?
  • A. Identifies and extracts specific information that should be processed.
  • B. Digitizes the document that should be processed.
  • C. Identifies words and their coordinates from images and PDFs.
  • D. Applies rules for validating that the information extracted from a document is correct.
Answer: A
Explanation:
Data Extraction identifies and extracts specific information from documents to be processed by automations.
This is a key part of UiPath's Document Understanding Framework, enabling bots to process structured and unstructured documents effectively.

NEW QUESTION # 127
Which of the following is a best practice when choosing a UiPath ML (Machine Learning) Extractor?
  • A. The size of the ML Extractor is the most important factor to consider when choosing an ML Extractor.Bigger models always perform better and provide more accurate extraction results because the development team invested time and effort into creating the algorithm, which in turn will result in better performance for the trained model.
  • B. Consider the document types, language, and data quality when choosing an ML Extractor.
    It is important to select one that is specifically trained or optimized for the document types being processed.
    It is also important to take into account the quality and diversity of the training data used to train the ML Extractor to ensure accurate and reliable extraction results.
  • C. The cost of the ML Extractor should be the main consideration when choosing an ML Extractor.
    Select the ML Extractor that offers the lowest price, regardless of its performance or suitability for the specific document understanding needs.
  • D. The popularity of the ML Extractor among other UiPath users should be the primary factor when choosing a UiPath ML Extractor.
    Opt for the ML Extractor that has the highest number of downloads or positive reviews.
Answer: B
Explanation:
The ML Extractor is a data extraction tool that uses machine learning models provided by UiPath to identify and extract data from documents. The ML Extractor can work with predefined document types, such as invoices, receipts, purchase orders, and utility bills, or with custom document types that are trained using the Data Manager and the Machine Learning Classifier Trainer12.
According to the best practice, the ML Extractor should be chosen based on the document types, language, and data quality of the documents being processed. It is important to select an ML Extractor that is specifically trained or optimized for the document types that are relevant for the use case, as different document types may have different layouts, fields, and formats. It is also important to take into account the language of the documents, as some ML Extractors may support only certain languages or require specific language settings. Moreover, it is important to consider the quality and diversity of the training data used to train the ML Extractor, as this may affect the accuracy and reliability of the extraction results. The training data should be representative of the real-world data, and should cover various scenarios, variations, and exceptions3.
References: 1: Machine Learning Extractor - UiPath Activities 2: Machine Learning Classifier Trainer - UiPath Document Understanding 3: Data Extraction - UiPath Document Understanding

NEW QUESTION # 128
What information should be filled in when adding an entity label for the OOB (Out Of the Box) labeling template?
  • A. Name. Input to be labeled. Attribute name. Shortcut, and Color.
  • B. Name, Shortcut, and Color.
  • C. Name. Data Type. Attribute name, and Color.
  • D. Name, Data Type. Attribute name. Shortcut, and Color.
Answer: A

NEW QUESTION # 129
......
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