Summer Special Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: exc65

examout.co

What does "k-shot prompting" refer to when using Large Language Models for task-specific applications?

A.

Providing the exact k words in the prompt to guide the model's response

B.

Explicitly providing k examples of the intended task in the prompt to guide the model’s output

C.

The process of training the model on k different tasks simultaneously to improve its versatility

D.

Limiting the model to only k possible outcomes or answers for a given task

How do Dot Product and Cosine Distance differ in their application to comparing text embeddings in natural language processing?

A.

Dot Product assesses the overall similarity in content, whereas Cosine Distance measures topical relevance.

B.

Dot Product is used for semantic analysis, whereas Cosine Distance is used for syntactic comparisons.

C.

Dot Product measures the magnitude and direction of vectors, whereas Cosine Distance focuses on the orientation regardless of magnitude.

D.

Dot Product calculates the literal overlap of words, whereas Cosine Distance evaluates the stylistic similarity.

Accuracy in vector databases contributes to the effectiveness of Large Language Models (LLMs) by preserving a specific type of relationship. What is the nature of these relationships, and why arethey crucial for language models?

A.

Linear relationships; they simplify the modeling process

B.

Semantic relationships; crucial for understanding context and generating precise language

C.

Hierarchical relationships; important for structuring database queries

D.

Temporal relationships; necessary for predicting future linguistic trends

Given the following prompts used with a Large Language Model, classify each as employing the Chain-of-Thought, Least-to-Most, or Step-Back prompting technique:

A.

"Calculate the total number of wheels needed for 3 cars. Cars have 4 wheels each. Then, use the total number of wheels to determine how many sets of wheels we can buy with $200 if one set (4 wheels) costs $50."

B.

"Solve a complex math problem by first identifying the formula needed, and then solve a simpler version of the problem before tackling the full question."

C.

"To understand the impact of greenhouse gases on climate change, let’s start by defining what greenhouse gases are. Next, we’ll explore how they trap heat in the Earth’s atmosphere."A. 1: Step-Back, 2: Chain-of-Thought, 3: Least-to-MostB. 1: Least-to-Most, 2: Chain-of-Thought, 3: Step-BackC. 1: Chain-of-Thought, 2: Step-Back, 3: Least-to-MostD. 1: Chain-of-Thought, 2: Least-to-Most, 3: Step-Back

How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models (LLMs) fundamentally alter their responses?

A.

It transforms their architecture from a neural network to a traditional database system.

B.

It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.

C.

It enables them to bypass the need for pretraining on large text corpora.

D.

It limits their ability to understand and generate natural language.

What is the purpose of frequency penalties in language model outputs?

A.

To ensure that tokens that appear frequently are used more often

B.

To penalize tokens that have already appeared, based on the number of times they have been used

C.

To reward the tokens that have never appeared in the text

D.

To randomly penalize some tokens to increase the diversity of the text