Analyzing Recency Bias in Language Models
Analyze the observed 'recency bias' in the provided case study from the perspectives of TWO different theoretical frameworks: one viewing the process as an optimization procedure, and the other viewing it as a form of belief updating. Explain how each framework would account for the model's final prediction being more aligned with the last example provided.
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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
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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A researcher observes that when a large language model is prompted with a few examples of input-output pairs that follow a simple linear pattern (e.g.,
Input: 2, Output: 5; Input: 3, Output: 7), it can accurately predict the output for a new input (e.g.,Input: 4, Output: 9). This behavior, where the model appears to fit a function to the provided data points without any changes to its underlying weights, lends the most direct support to which theoretical interpretation of this phenomenon?Match each theoretical interpretation of how a language model learns from examples in its prompt with the description of its core mechanism.
Analyzing Recency Bias in Language Models