Phil 1.13.2022




  • Standup was cancelled for today

GPT Agents

  • Made good progress yesterday
  • Continue on interpolation section. Set up the pretrained average stars in a table and drop the figure. Show the bar chart and Pearson’s
  • Add comparison of GPT and GPT(v). Chart? Table? And show Pearson’s
  • 1:00 – 2:30 Meeting
    • Good progress. I need to do for the three star rating category:   
      • compute an error metric (L1 difference) for the estimated proportion of positive reviews for “gray bars” (GPT with the reviews containing the keywords held out) vs the ground truth “blue bars” . Report this error metric in a table (performance of our method).   
      • simulate the empirical count baseline method in the low data scenario: draw a small number of reviews containing the keyword, let’s say 6 of them). Compute the error metric (L1 difference) for the empirical counts baseline, computed on this subset, vs the ground truth “blue bars”. Repeat this many  times (say, 10,000 times). Report the average error metric in a table (performance of the baseline method).
    • Finished the data extraction. Now I have to make spreadsheets and charts