From understanding there r 2 parts of it, 1. LLM-as-a-judge, to generate reward score. As first step evaluate this strategy can help during re-generation request with exhaustive beam search. <img width="1056" alt="Screen Shot 2024-01-22 at 1 27 14 PM" src="https://github.com/h2oai/sql-sidekick/assets/1318029/0ad74c43-45df-4019-b063-c87e13b28a6d"> 2. Self-training/modification on preference pairs #Reference: https://arxiv.org/abs/2401.10020
From understanding there r 2 parts of it,
#Reference: https://arxiv.org/abs/2401.10020