Our experiments and analysis reveal that, unlike CoT-
based methods, LoT cannot be directly achieved by prompt-
ing alone. This is because the inherent reasoning capabil-
ities and extensive knowledge of LLMs are not sufficient
to enable LoT ability. However, when trained with our
proposed CLoT method, LLMs can effectively engage in
a range of creative tasks. Additionally, the use of specific
prompting techniques can enhance the LoT ability of CLoT-
trained LLMs. These findings suggest that LoT could po-
tentially be considered an additional general reasoning abil-
ity for LLMs that is not contained in current LLMs.
5.3. Human Evaluation
We conduct a user preference study to test creativity of
LLMs. Here we select six LLMs to generate responses for
a total of eighteen questions across three tasks (IT2T, I2T
and T2T). We use choice questions, and ask users to choose
the most creative and humorous responses. Fig. 7 summa-
rizes the statistical analysis of 154 valid surveys. The re-
Let’sThinkOutsidetheBox