Improve Preference Elicitation

README.md

@@ -86,7 +86,9 @@ Newt Figure presents a violin plot illustrating the share of the
 total amount (\$100) that the dictator allocates to themselves for each model.
 The median share taken by <tt>GPT-4.5</tt>, <tt>Llama3</tt>,
 <tt>Mistral-Small</tt>, and <tt>DeepSeek-R1</tt> through one-shot decisions is
-\$50, likely due to a corpus-based biases like term frequency. When we ask the
+\$50, likely due to a corpus-based biases like term frequency. 
+The median share taken by <tt>mixtral:8x7b</tt>, <tt>Llama3.3:latest</tt>,
+is \$60. When we ask the
 models to generate a strategy rather than a one-shot action, all models
 distribute the amount equally, except <tt>GPT-4.5</tt>, which retains about
 $70\%$ of the total amount. Interestingly, under these standard conditions,
@@ -99,7 +101,6 @@ preferences, or contexts.
 
 ![Violin Plot of My Share for Each Model](figures/dictator/dictator_violin.svg)
 
-
 Our sensitivity analysis of the temperature parameter reveals that the portion
 retained by the dictator remains stable. However, the decisions become more
 deterministic at low temperatures, whereas allocation diversity increases at