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An AI alignment team is evaluating a language model's response using three distinct reward models: Helpfulness, Harmlessness, and Conciseness. For a specific response, the models provide the following scores and are assigned the following weights:
- Helpfulness: Score = 8.0, Weight = 2.0
- Harmlessness: Score = 9.0, Weight = 3.0
- Conciseness: Score = 6.0, Weight = 1.0
Using the weighted average formula for combining rewards, what is the final aggregated reward score for this response? (Assume K is the total number of models).
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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Using Combined Reward for Policy Supervision
An AI alignment team is evaluating a language model's response using three distinct reward models: Helpfulness, Harmlessness, and Conciseness. For a specific response, the models provide the following scores and are assigned the following weights:
- Helpfulness: Score = 8.0, Weight = 2.0
- Harmlessness: Score = 9.0, Weight = 3.0
- Conciseness: Score = 6.0, Weight = 1.0
Using the weighted average formula for combining rewards, what is the final aggregated reward score for this response? (Assume K is the total number of models).
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