I got the highest score on ARC-AGI again swapping Python for English
11 hours ago
- #AI
- #Machine Learning
- #ARC-AGI
- ARC-AGI is a benchmark for abstract pattern recognition, highlighting the gap between human and AI performance.
- The author achieved a new high score of 79.6% on ARC v1 and 29.4% on ARC v2 using Evolutionary Test-Time Compute with English instructions.
- The method involves generating and refining natural language instructions through evolutionary cycles, replacing Python functions.
- ARC-AGI v2 tasks are more complex, requiring multi-step reasoning, yet remain solvable by humans with high accuracy.
- Current LLMs struggle with 'dead reasoning zones,' where logic fails inconsistently across domains.
- The author suggests that reinforcement learning (RL) can help models develop consistent, transferable reasoning skills.
- AGI, as defined by François Chollet, requires efficient skill acquisition outside training data, a goal not yet met by LLMs.