Apr 23
Text-to-Distribution Prediction with Quantile Tokens and Neighbor Context
★★★★★
significance 3/5
The paper introduces Quantile Token Regression, a method to improve LLM-based text regression by inserting dedicated quantile tokens into the input sequence. This approach uses neighbor context and retrieval to better predict full conditional distributions rather than single point values.
Why it matters
Refining how LLMs map text to probability distributions could bridge the gap between linguistic generation and precise statistical forecasting.
Tags
#llm #regression #quantile tokens #distributional predictionRelated coverage
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