XXXFLAN. Hence, we denote the resulting pairs as

2https://en.wikipedia.org/wiki/Category:

Machine_learning

{(cid:98)XXXP3,(cid:98)YYY P3}, (cid:98)DDDFLAN = {(cid:98)XXXFLAN,(cid:98)YYY FLAN}, (cid:98)DDDA =
{(cid:98)XXXA,(cid:98)YYY A}, DDDP3 = {XXXP3, YYY P3} and DDDFLAN =

{XXXFLAN, YYY FLAN}.3 The complete dataset DDDALL
is the union of all the aforementioned instruction-
response pairs.

3.3 Exploratory Data Analysis
In this section, we conduct an exploratory analysis
of the generated text. Our analysis focuses on sev-
eral aspects of the dataset, including basic statistics,
diversity, and human evaluation.
3.3.1 Statistics
We present the dataset statistics in Table 1. As
we claimed before, gpt-3.5-turbo often fails to
provide the necessary context for the generated in-

struction, given that the average length of (cid:98)XXXP3 and
(cid:98)XXXFLAN is signiﬁcantly short than that of XXXP3 and
LaMini-LM- A Diverse Herd of Distilled Models from Large-Scale Instructions