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Using Beam Search to Generate Multiple Outputs
A practical example of sampling from the hypothesis space involves using the beam search decoding algorithm. Instead of selecting only the top-scoring hypothesis, multiple outputs can be generated by collecting all the complete hypotheses that are maintained within the beam during the search process.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Computing Sciences
Foundations of Large Language Models Course
Related
Modifying Search Algorithms for Enhanced Sampling
Adjusting Temperature for Output Diversity
A developer is using a text-generation model to brainstorm a list of potential taglines for a new product. They provide a single, well-crafted prompt but find that the model consistently produces the same tagline. To generate a variety of different, high-quality taglines from this one prompt, which approach directly leverages the model's ability to consider multiple potential outcomes?
Optimizing a Content Generation System
Generating Creative Variations
Example of Generating Multiple Responses via LLM Sampling
Learn After
An engineer is using a text generation model with a beam search decoding strategy where the beam width is set to 3. The goal is to generate a list of possible sentence completions. At a certain step, the algorithm has produced the following partial sentences (hypotheses) with their associated scores (higher is better):
- "The cat sat on the mat" (Score: -0.8) [This is a complete sentence]
- "The cat sat on the rug" (Score: -1.2)
- "The cat sat on the chair" (Score: -1.5)
- "The cat sat on t
Generating Multiple Outputs from a Decoding Algorithm
A text generation algorithm is configured to produce multiple, distinct sentences by exploring several possibilities at once. At each step, it maintains a set of the most likely partial sentences. Arrange the following actions in the correct order to describe a single cycle of this process, which is repeated until the desired number of complete sentences is found.