has a shape of a cat, and the one in Fig. 9 (d) is similar
to a human. These white cloud images are generated by a
control diffusion model [31, 32, 84, 85], guided by masks
shown in Fig. 9 (b). We use top-1 accuracy as metric. See
more details in Appendix. For DAT, it is a classic creativ-
ity test [33, 86] which needs participants to choose words
with larger semantic distances among 10 unrelated nouns.
Here for test easily, we transfer the DAT benchmark [33]
to a series of choice questions and take the standard aver-
age semantic distance (ASD) as a metric. These questions
can challenge the LLM to select the one word from nine
options that differs from the given word most. See more de-
tails in Appendix. CGG and DAT can test the LoT ability of
LLMs, specifically their remote association thinking ability,
and provide quite different evaluation platforms. As shown
in Fig. 9 (e-f), CLoT can also significantly enhance the per-
formance of the SoTA Qwen-VL on both CGG and DAT
Let’sThinkOutsidetheBox