A company is working on a large language model (LLM) and noticed that the LLM's outputs are not as diverse as expected. Which parameter should the company adjust?

The correct answer is A. Temperature. The “temperature” parameter controls the randomness and diversity of outputs generated by a large language model. Increasing the temperature produces more diverse and creative responses, while lowering it makes the outputs more focused and deterministic.

Submitted by viktor_hu· Mar 30, 2026Fundamentals of Generative AI

Question

A company is working on a large language model (LLM) and noticed that the LLM’s outputs are not as diverse as expected. Which parameter should the company adjust?

Options

ATemperature
BBatch size
CLearning rate
DOptimizer type

How the community answered

(39 responses)

A
74% (29)
B
8% (3)
C
13% (5)
D
5% (2)

Explanation

The “temperature” parameter controls the randomness and diversity of outputs generated by a large language model. Increasing the temperature produces more diverse and creative responses, while lowering it makes the outputs more focused and deterministic.

Topics

#temperature#output diversity#LLM inference parameters#text generation

Community Discussion

No community discussion yet for this question.

Full AIF-C01 Practice