Abstract: In one embodiment, a non-transitory computer-readable media stores instructions executable by processors for generating a prompt configured for eliciting outputs from large language models (LLMs) based on information associated with a task, inputting the prompt to a first LLM configured to output a response based on processing the prompt, determining metrics for evaluating the first LLM based on the task, wherein each of the metrics is associated with a scoring guideline, generating metric prompts based on the respective metrics and the scoring guidelines associated with the respective metrics, inputting the response and the metric prompts to second LLMs configured to output scores corresponding to the respective metrics based on processing the response and the metric prompts, and generating an analysis report based on the metrics and their corresponding scores.

Abstract: In one embodiment, a non-transitory computer-readable media stores instructions executable by processors for generating a prompt configured for eliciting outputs from large language models (LLMs) based on information associated with a task, inputting the prompt to a first LLM configured to output a response based on processing the prompt, determining metrics for evaluating the first LLM based on the task, wherein each of the metrics is associated with a scoring guideline, generating metric prompts based on the respective metrics and the scoring guidelines associated with the respective metrics, inputting the response and the metric prompts to second LLMs configured to output scores corresponding to the respective metrics based on processing the response and the metric prompts, and generating an analysis report based on the metrics and their corresponding scores.

Abstract: Techniques for constructing padding-sensitive batches for text recognition are provided. In one technique, a first bounding box from a list of bounding boxes is added or included into a batch of zero or more bounding boxes. Each bounding box in the list of bounding boxes surrounds different detected text in a digital image. A second bounding box is identified from the list. The second bounding box is wider than the first bounding box. A difference between (1) a width of the second bounding box and (2) a particular width is determined. The particular width is based on a width of a bounding box in the batch. Based on the difference and a threshold value, it is determined whether to include the second bounding box in the batch. The batch is then input into a test recognition model.