I want to start by expressing my sincere appreciation for this project. It has been instrumental in advancing my experiments, and I am genuinely grateful for the work you've put into developing such a powerful tool.
As I've integrated guidance into my workflows, I've encountered a scenario where an enhancement could significantly augment its utility, specifically regarding the select function and the associated confidence in its outputs.
Current Limitation
When utilizing the select function to present the model with multiple choices (e.g., "Which one do you think is more appropriate? A, B, C, None of the above"), the model invariably selects one of the provided options with a default confidence score of 1. This behavior implies a certainty that may not always align with the model's actual predictive confidence, especially in scenarios where the most accurate answer might be "None of the above." The current mechanism does not accommodate the expression of uncertainty or the preference for an option outside the provided list.
Proposed Feature
I propose the introduction of a feature that provides confidence scores for the outputs generated by the select function. This enhancement would not only indicate the model's chosen option but also reflect how confident it is in that selection. Such a feature would be invaluable for cases where the correct answer might not be explicitly listed among the options, enabling the model to suggest "None of the above" with a corresponding confidence level.
Benefits
Enhanced Decision Making: Users can make more informed decisions based on the model's confidence level, understanding when the model is less certain and thereby considering alternative sources of information or further investigation.
Increased Flexibility: This feature would allow for more nuanced interactions with the model, accommodating scenarios where the best answer isn't among the predefined choices.
Improved User Experience: By providing a clearer picture of the model's assessment, users can better gauge the reliability of the output, leading to increased trust and satisfaction with the system.
shawnz
commented
4 months ago
I want to start by expressing my sincere appreciation for this project. It has been instrumental in advancing my experiments, and I am genuinely grateful for the work you've put into developing such a powerful tool.
As I've integrated guidance into my workflows, I've encountered a scenario where an enhancement could significantly augment its utility, specifically regarding the
selectfunction and the associated confidence in its outputs.Current Limitation
When utilizing the
selectfunction to present the model with multiple choices (e.g., "Which one do you think is more appropriate? A, B, C, None of the above"), the model invariably selects one of the provided options with a default confidence score of 1. This behavior implies a certainty that may not always align with the model's actual predictive confidence, especially in scenarios where the most accurate answer might be "None of the above." The current mechanism does not accommodate the expression of uncertainty or the preference for an option outside the provided list.Proposed Feature
I propose the introduction of a feature that provides confidence scores for the outputs generated by the select function. This enhancement would not only indicate the model's chosen option but also reflect how confident it is in that selection. Such a feature would be invaluable for cases where the correct answer might not be explicitly listed among the options, enabling the model to suggest "None of the above" with a corresponding confidence level.
Benefits