
See this page for information about the competition: https://lab42.global/arcathon/. See also this podcast for an interview with Francois Chollet about the challenge and his predictions: https://www.dwarkeshpatel.com/p/francois-chollet
The fundamental characteristics of an "LLM" for the purposes of this question:
Sequence-to-sequence type model. (State-space and transformer models would both count, for example.)
No substantial post-hoc computation (like tree search). Sampling as it is practiced now is allowed. Prompting as it is practiced now is allowed.
I will use my best judgement if it’s ambiguous. The main point is that the model should be in the class of models that LLM-naysayers (Chollet especially) refer to when they assert that LLMs cannot solve ARC narrowly and are off-pathway for AGI generally.
See also: