The ARC-AGI benchmark (and associated ARC Prize) are widely considered by top AI experts as one of, if not the best, benchmarks for measuring AGI progress.

Question

BlackTom AI · Accepted Answer

ARC-AGI (the Abstraction and Reasoning Corpus and its associated prize) is a set of small, human-designed tasks created to probe abstract pattern recognition and generalization across novel problems. It was proposed as a probe of “general intelligence” because solutions require forming abstractions and applying them to new instances rather than memorizing training data.

Relevant knowledge points:
- ARC’s design goal: test compositional abstraction and generalization on visually simple toy tasks.
- Benchmarks for AGI progress are judged on coverage (breadth of abilities), scale, robustness, and community adoption.
- Criticisms of ARC include small problem set size, human-engineered tasks that favor specific heuristics or program synthesis, poor coverage of language, social, motor, and real-world reasoning abilities, and susceptibility to overfitting with domain-specific solvers.
- The AI community uses many benchmarks (GLUE/SuperGLUE, BIG-bench, robotics suites, multi-modal tasks); no single benchmark is accepted as “best.”

Step-by-step reasoning:
1. ARC measures a narrow slice of cognition (abstraction on grid puzzles) rather than the full spectrum of capabilities expected of AGI (language, planning, learning across modalities, real-world interaction).
2. Because of this narrow scope and the small corpus size, high performance on ARC does not imply broad AGI competence. Researchers have shown program-synthesis or domain-specific heuristics can perform well without general intelligence.
3. The ARC Prize incentivizes work on this class of problems but has not produced consensus that ARC is the definitive AGI metric; many experts treat it as one interesting challenge among many.
4. The field prefers a portfolio of benchmarks covering multiple modalities and tasks; thus no single benchmark (including ARC) is widely accepted as the best.

Why the correct answer is correct:
The statement asserts wide consensus among top experts that ARC-AGI is among the best AGI benchmarks. Given ARC’s narrow scope, well-known criticisms, and the field’s reliance on multiple complementary benchmarks, that assertion is false.

Why “True” is incorrect:
“True” would require broad expert agreement and community adoption of ARC as a premier AGI benchmark, which does not exist.

Conclusion: The correct answer is False, matching the provided answer.

The ARC-AGI benchmark (and associated ARC Prize) are widely considered by top AI experts as one of, if not the best, benchmarks for measuring AGI progress.判断题

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