Summary of Capturing Sparks Of Abstraction For the Arc Challenge, by Martin Andrews
Capturing Sparks of Abstraction for the ARC Challenge
by Martin Andrews
First submitted to arxiv on: 17 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed approach aims to advance the solution of ARC Challenge problems, which have seen significant progress recently. However, it appears that new methods are necessary to surpass 60% accuracy. Even commercial Large Language Models (LLMs) struggle to comprehend many problems when provided with input and output grids, rendering LLM-led program search ineffective in discovering solutions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Recent breakthroughs in solving ARC Challenge problems have been impressive, but it seems that new techniques are needed to push beyond 60% accuracy. Even commercial Large Language Models (LLMs) struggle to understand many of the problems when given input and output grids, making it challenging to discover solutions through LLM-led program search. |
