Estimating these metrics for human-generated responses: We ask crowdworkers to respond to randomly selected
samples of the evaluation datasets (labeled as ‘Human’ in 1, 4 and 5). The crowdworkers are explicitly informed to
reply in a safe, sensible, speciﬁc, interesting, grounded, and informative manner. They are also explicitly asked to
use any external tools necessary to generate these responses (e.g., including an information retrieval system). The
context-response pairs are then sent for evaluation, and a consensus label is formed by majority voting, just as for model
generated responses.

6 LaMDA ﬁne-tuning

6.1 Discriminative and generative ﬁne-tuning for Quality (SSI) and Safety
LaMDA- Language Models for Dialog Applications