arXiv AI
Jul 3
CreativityPrism: A Cross-Domain Evaluation Framework for Large Language Model Creativity
arXiv:2510. 20091v3 Announce Type: replace-cross Abstract: Creativity is often seen as a hallmark of human intelligence.
Creative Integration: A Decidable Criterion of Creativity
arXiv:2606. 13977v1 Announce Type: cross Abstract: "Integrative" solutions are widely praised but rarely defined: we lack an operational way to tell a genuine integration -- one that makes the world cheaper to describe -- from a tidy re-description.
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arXiv AI
Jun 11
Automated Creativity Evaluation of Language Models Across Open-Ended Tasks
arXiv:2606. 11762v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable progress in language understanding, reasoning, and generation, sparking growing interest in their creative potential.
arXiv AI
Jun 16
LLM Jaggedness Unlocks Scientific Creativity
arXiv:2605. 10574v3 Announce Type: replace Abstract: As artificial intelligence advances, models are not improving uniformly.
arXiv Computation and Language
Sep 4
Decoupled Analysis-Judging: An Automated Creativity Evaluator Using LLMs in Complex Multi-step Creativity Tasks
The paper introduces CreaEval, an automated creativity evaluator designed for complex multi-step tasks (CGPST). It separates the evaluation process into two phases: a memory‑augmented analysis that transforms responses into structured evidence, and an evidence‑based judging step that scores without seeing raw outputs. Experiments show CreaEval outperforms existing baselines by an average of 22.74% across CGPST and two simpler creativity tasks.
Hugging Face Trending Papers
Jun 10
Automated Creativity Evaluation of Language Models Across Open-Ended Tasks
Large language models (LLMs) have achieved remarkable progress in language understanding, reasoning, and generation, sparking growing interest in their creative potential. Realizing this potential requires systematic and scalable methods for evaluating creativity across diverse tasks.
arXiv AI
Jun 19
Creativity Reconsidered: Generative AI and the Problem of Intentional Agency
arXiv:2601. 15797v2 Announce Type: replace Abstract: Many theorists maintain that conscious intentional agency is a necessary condition of creativity.
arXiv Computation and Language
Sep 22
Is Imagination Derived from Hallucination? A Cross-Taxonomy Evaluation of Imagination and Hallucination in Large Language Models
arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative c...
arXiv AI
Jun 15
Under What Conditions Can a Machine Be Called Genuinely Creative?
arXiv:2606. 13196v2 Announce Type: replace Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
arXiv AI
Jun 12
Under What Conditions Can a Machine Become Genuinely Creative?
arXiv:2606. 13196v1 Announce Type: new Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
arXiv AI
Aug 10
Can MLLMs Decode the Creative Leap? Introducing C4 for Cross-Concept Understanding
arXiv:2608. 06501v1 Announce Type: new Abstract: Creative capabilities of MLLMs matter in design, communication, education, and human--AI collaboration, yet remain difficult to evaluate because explicit targets and reward signals are scarce compared with accuracy-oriented tasks.
arXiv AI
Jul 21
ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation
arXiv:2601. 07121v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used not only for problem solving but also for creative ideation; however, generating ideas that are both novel and coherent remains challenging.
arXiv AI
Jun 12
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges
arXiv:2603. 11863v2 Announce Type: replace Abstract: The saturation of high-quality pre-training data has shifted research focus toward evolutionary systems capable of continuously generating novel artifacts, leading to the success of AlphaEvolve.