Câu 13: UiAAAv1: UiPath Agentic Automation Associate v1.0
A developer is working on fine-tuning an LLM for generating step-by-step automation guides. After providing a detailed example prompt, they notice inconsistencies in the way the LLM interprets certain technical terms. What could be the reason for this behavior?
Nội dung câu hỏi
A developer is working on fine-tuning an LLM for generating step-by-step automation guides. After providing a detailed example prompt, they notice inconsistencies in the way the LLM interprets certain technical terms. What could be the reason for this behavior?
Các lựa chọn
Đáp án được giữ gọn theo nhãn A, B, C, D trong phần bình chọn tương tác.
- A. The LLM’s tokenization process may have split complex technical terms into multiple tokens, causing slight variations in how the model interprets and weights their relationships within the context of the prompt. — đáp án hiện tại
- B. The LLM’s interpretation is solely based on the frequency of terms within the training dataset, rendering technical nuances irrelevant during generation.
- C. The inconsistency is related to the token limit defined for the prompt’s length, which affects the LLM’s ability to complete a response rather than its understanding of technical terms.
- D. The LLM does not rely on tokenization for understanding prompts; instead, misinterpretation arises from inadequate pre-programmed definitions of technical terms.
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