arXiv subjects

Uğur Önal

Publications and source records attributed to Uğur Önal.

3 recordsLinked to original sources

arXiv2026

Hybrid Intelligence in Cartoon Captioning: Evaluating AI as a Creative Writing Partner

Crafting cartoon captions requires an understanding of humor, context, and the relationship between image and text. Traditionally, illustrators and writers collaborate to strengthen visual storytelling and comedic timing. With advances in natural language generation, Large Language Models (LLMs) can assist in this process. This study examines AI's role in caption generation by testing GPT-4o via the ChatGPT interface on IEEE Computer magazine cartoons. By removing captions and prompting AI to generate replacements, we assess its ability to produce jokes that match the depicted situation and narrative intent. Our findings show that while AI-generated captions are often humorous and contextually relevant, they sometimes diverge from the cartoon's intended meaning, for example, by missing irony, cultural references, or contextual constraints. However, AI can also produce alternatives that broaden creative exploration and occasionally improve upon the original humor. We argue that current AI systems are best used as an assistant rather than a replacement for human creativity. By integrating AI-generated suggestions, cartoonists can explore diverse humor styles, streamline ideation, and refine final captions while retaining creative control. This study highlights AI's potential as a practical tool for caption ideation within a hybrid human-AI workflow.

cs.HC↗

arXiv2026

Twisted Edges: A Unified Framework for Designing Linked Knot (LK) Structures Using Labeled Non-Manifold Surface Meshes

We present Twisted Edges, a unified framework for designing Linked Knot (LK) structures using labeled non-manifold surface meshes. While the concept of edge twists, originating in topological graph theory, is foundational to these designs, prior approaches have been strictly limited to binary states. We identify this restriction as a critical barrier; binary twisting fails to capture the full spectrum of topological possibilities, rendering a vast class of structural and dynamic behaviors inaccessible. To overcome this limitation, we generalize the twist formulation to support arbitrary integer twist labels. This expansion reveals that while zero twists may introduce disconnections, applying even twists to 2-manifold meshes robustly preserves connectivity, transforming surfaces into fully connected, chainmail-like structures where faces form consistently linked cycles. Furthermore, we extend this framework to non-manifold meshes, where specific integer assignments prevent cycle merging. This capability, unattainable with binary methods, enables the design of partial connectivity and functional hinges, supporting dynamic folding and articulation. Theoretically, we show that these integer-twisted meshes correspond to knotted surfaces in four dimensions, with LK structures arising as their immersions into $\mathbb{R}^3$. By breaking the binary constraint, this work establishes a coherent paradigm for the systematic exploration of previously unstudied woven and articulated structures.

cs.GR↗

arXiv2025

Comparing Human and AI Performance in Visual Storytelling through Creation of Comic Strips: A Case Study

This article presents a case study comparing the capabilities of humans and artificial intelligence (AI) for visual storytelling. We developed detailed instructions to recreate a three-panel Nancy cartoon strip by Ernie Bushmiller and provided them to both humans and AI systems. The human participants were 20-something students with basic artistic training but no experience or knowledge of this comic strip. The AI systems used were popular commercial models trained to draw and paint like artists, though their training sets may not necessarily include Bushmiller's work. Results showed that AI systems excel at mimicking professional art but struggle to create coherent visual stories. In contrast, humans proved highly adept at transforming instructions into meaningful visual narratives.

cs.HC↗