Buchumschlag

Beyond Divergent Creativity: A Human-Based Evaluation of Creativity in Large Language Models

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Nakajima, Kumiko, Zuiderveld, Jan, Pezzelle, Sandro
Format:	Preprint
Veröffentlicht:	2026
Schlagworte:	Computation and Language
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Divergent Creativity in Humans and Large Language Models
von: Bellemare-Pepin, Antoine, et al.
Veröffentlicht: (2024)

CreativityPrism: A Holistic Evaluation Framework for Large Language Model Creativity
von: Hou, Zhaoyi Joey, et al.
Veröffentlicht: (2025)

Evaluating Creative Short Story Generation in Humans and Large Language Models
von: Ismayilzada, Mete, et al.
Veröffentlicht: (2024)

How Language Models Conflate Logical Validity with Plausibility: A Representational Analysis of Content Effects
von: Bertolazzi, Leonardo, et al.
Veröffentlicht: (2025)

Do Pre-Trained Language Models Detect and Understand Semantic Underspecification? Ask the DUST!
von: Wildenburg, Frank, et al.
Veröffentlicht: (2024)

Naming, Describing, and Quantifying Visual Objects in Humans and LLMs
von: Testoni, Alberto, et al.
Veröffentlicht: (2024)

On the Creativity of Large Language Models
von: Franceschelli, Giorgio, et al.
Veröffentlicht: (2023)

On Recipe Memorization and Creativity in Large Language Models: Is Your Model a Creative Cook, a Bad Cook, or Merely a Plagiator?
von: Kvapil, Jan, et al.
Veröffentlicht: (2025)

Vision-Language Models Align with Human Neural Representations in Concept Processing
von: Bavaresco, Anna, et al.
Veröffentlicht: (2024)

Steering Large Language Models to Evaluate and Amplify Creativity
von: Olson, Matthew Lyle, et al.
Veröffentlicht: (2024)

Automated Creativity Evaluation for Large Language Models: A Reference-Based Approach
von: Li, Ruizhe, et al.
Veröffentlicht: (2025)

Characterising the Creative Process in Humans and Large Language Models
von: Nath, Surabhi S., et al.
Veröffentlicht: (2024)

A Comparative Approach to Assessing Linguistic Creativity of Large Language Models and Humans
von: Dinu, Anca, et al.
Veröffentlicht: (2025)

Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms
von: Hanna, Michael, et al.
Veröffentlicht: (2024)

CreativEval: Evaluating Creativity of LLM-Based Hardware Code Generation
von: DeLorenzo, Matthew, et al.
Veröffentlicht: (2024)

The BLA Benchmark: Investigating Basic Language Abilities of Pre-Trained Multimodal Models
von: Chen, Xinyi, et al.
Veröffentlicht: (2023)

Rethinking Creativity Evaluation: A Critical Analysis of Existing Creativity Evaluations
von: Lu, Li-Chun, et al.
Veröffentlicht: (2025)

Evaluating Text Creativity across Diverse Domains: A Dataset and Large Language Model Evaluator
von: Cao, Qian, et al.
Veröffentlicht: (2025)

Assessing and Understanding Creativity in Large Language Models
von: Zhao, Yunpu, et al.
Veröffentlicht: (2024)

Is Temperature the Creativity Parameter of Large Language Models?
von: Peeperkorn, Max, et al.
Veröffentlicht: (2024)

Describing Images $\textit{Fast and Slow}$: Quantifying and Predicting the Variation in Human Signals during Visuo-Linguistic Processes
von: Takmaz, Ece, et al.
Veröffentlicht: (2024)

Large Language Models Align with the Human Brain during Creative Thinking
von: Ismayilzada, Mete, et al.
Veröffentlicht: (2026)

SimulBench: Evaluating Language Models with Creative Simulation Tasks
von: Jia, Qi, et al.
Veröffentlicht: (2024)

Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations
von: Gerrits, Kyo, et al.
Veröffentlicht: (2026)

Who is the richest club in the championship? Detecting and Rewriting Underspecified Questions Improve QA Performance
von: Huang, Yunchong, et al.
Veröffentlicht: (2026)

They want to pretend not to understand: The Limits of Current LLMs in Interpreting Implicit Content of Political Discourse
von: Paci, Walter, et al.
Veröffentlicht: (2025)

How Creative Are Large Language Models in Generating Molecules?
von: Tao, Wen, et al.
Veröffentlicht: (2026)

Large Language Models for Scientific Idea Generation: A Creativity-Centered Survey
von: Shahhosseini, Fatemeh, et al.
Veröffentlicht: (2025)

Inducing Sustained Creativity and Diversity in Large Language Models
von: Luo, Queenie, et al.
Veröffentlicht: (2026)

How do Humans and Language Models Reason About Creativity? A Comparative Analysis
von: Laverghetta Jr., Antonio, et al.
Veröffentlicht: (2025)

MacGyver: Are Large Language Models Creative Problem Solvers?
von: Tian, Yufei, et al.
Veröffentlicht: (2023)

Can AI Be as Creative as Humans?
von: Wang, Haonan, et al.
Veröffentlicht: (2024)

Art or Artifice? Large Language Models and the False Promise of Creativity
von: Chakrabarty, Tuhin, et al.
Veröffentlicht: (2023)

CreativityBench: Evaluating Agent Creative Reasoning via Affordance-Based Tool Repurposing
von: Qian, Cheng, et al.
Veröffentlicht: (2026)

Deep Associations, High Creativity: A Simple yet Effective Metric for Evaluating Large Language Models
von: Qiu, Ziliang, et al.
Veröffentlicht: (2025)

Not (yet) the whole story: Evaluating Visual Storytelling Requires More than Measuring Coherence, Grounding, and Repetition
von: Surikuchi, Aditya K, et al.
Veröffentlicht: (2024)

Base Models Beat Aligned Models at Randomness and Creativity
von: West, Peter, et al.
Veröffentlicht: (2025)

Natural Language Generation from Visual Events: State-of-the-Art and Key Open Questions
von: Surikuchi, Aditya K, et al.
Veröffentlicht: (2025)

Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextually Important Moments
von: Surikuchi, Aditya K, et al.
Veröffentlicht: (2026)

Enhancing Creativity in Large Language Models through Associative Thinking Strategies
von: Mehrotra, Pronita, et al.
Veröffentlicht: (2024)