strated in the Text-to-Video gallery in Figure 2. This
includes models such as Make-A-Video [37], Tune-A-
Video [44], Text2Video-Zero [17], VideoCrafter [7], Zero-
Scope [26] and others. More importantly, should more ad-
vanced models be integrated into the Text-to-Video gallery
in the future, GPT4Video will seamlessly adapt without
necessitating any modifications.
In contrast, the current
method of integrating “generative vokens” only accommo-
dates one specific text-to-video model per training session.
This limitation arises because different text-to-video models
may utilize various Text encoders. In this work, we employ
ZeroScope [26] 1 as our video generation model.
3.5. Safety Alignment
For multimodal large language models, ensuring the gen-
eration of both useful and safe content, especially visuals,
is imperative for their broad adoption. Take the handling
of sexually explicit content as an example: Current text-
to-image models employ an ancillary NSFW (Not Safe For
GPT4Video