Symbol r
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normalizing each sampled response’s reward against the mean and standard deviation of a group of G responses to the same prompt rather than against a separately trained critic network [ 13 ] . Lambert and colleagues, building the fully open Tulu 3 post-training recipe, named the general approach explicitly, describing it as “a novel method we call Reinforcement Learning with Verifiable Rewards,” and used it alongside supervised fine-tuning and preference optimization rather than as a wholesale replacement for either [ 15 ] . The clearest large-scale demonstration is DeepSeek-R1: Guo and colleagues report training a model with reinforcement learning alone against a purely rule-based reward —…
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Symbol x
x is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.
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y is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.
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tar is an input to the expression that computes the quantity on the left.
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Equation 25 · AI Safety
The Main Technical Approaches to AI Alignment, Compared
This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.
normalizing each sampled response’s reward against the mean and standard deviation of a group of G responses to the same prompt rather than against a separately trained critic network [ 13 ] . Lambert and colleagues, building the fully open Tulu 3 post-training recipe, named the general approach explicitly, describing it as “a novel method we call Reinforcement Learning with Verifiable Rewards,” and used it alongside supervised fine-tuning and preference optimization rather than as a wholesale replacement for either [ 15 ] . The clearest large-scale demonstration is DeepSeek-R1: Guo and colleagues report training a model with reinforcement learning alone against a purely rule-based reward —…
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