arXiv:2607.01152v1 Announce Type: new Abstract: Creativity research has debated whether creativity is domain-specific (e.g., visual, writing, science), and if it is psychometrically separable from general intelligence. Both questions now apply to LLMs, but a unified benchmark of AI creativity remains elusive. We introduce AGC-Bench, an artificial general creativity benchmark built from a systematic review of the AI creativity literature (3,101 papers screened, 497 benchmarks identified), paired with an agentic harness that converts idiosyncratic codebases into HELM-standardized benchmarks. The
The proliferation of advanced LLMs necessitates standardized, robust benchmarks beyond traditional intelligence tests to assess complex cognitive abilities like creativity, which is increasingly viewed as a critical next frontier for AI. This development arrives as the AI community grapples with defining and measuring the generalized capabilities of AI systems.
A strategic reader should care because establishing a unified benchmark for Artificial General Creativity (AGC-Bench) will accelerate the development of more sophisticated AI models and allow for clearer comparisons and assessments of their evolving intellectual capabilities. This benchmark could become a critical standard for evaluating the advancement of foundation models beyond mere task performance to more nuanced, human-like cognitive functions.
The introduction of AGC-Bench shifts the focus of AI evaluation beyond general intelligence to include quantifiable assessments of creativity, providing a new metric for comparing and improving AI systems. This moves the conversation from 'can AI perform tasks' to 'can AI generate novel, valuable ideas uniquely'.
- · AI research institutions
- · Developers of creative AI tools
- · Generative AI platforms
- · AI benchmark developers
- · AI models lacking creative capacities
- · Companies relying on opaque AI evaluation methods
The benchmark provides a standardized way to measure AI creativity, enabling clearer competitive analysis among AI models.
Improved creative AI could lead to widespread disruption in creative industries, from content generation to scientific discovery.
The pursuit of Artificial General Creativity might reveal fundamental insights into human cognition and the nature of intelligence itself.
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