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Recent technological advances popularized the use of image generation among the general public. Crafting effective prompts can, however, be difficult for novice users. To tackle this challenge, we developed PromptMap, a new interaction…

Utilizing Large Language Models (LLMs) for complex tasks is challenging, often involving a time-consuming and uncontrollable prompt engineering process. This paper introduces a novel human-LLM interaction framework, Low-code LLM. It…

计算与语言 · 计算机科学 2024-04-02 Yuzhe Cai , Shaoguang Mao , Wenshan Wu , Zehua Wang , Yaobo Liang , Tao Ge , Chenfei Wu , Wang You , Ting Song , Yan Xia , Jonathan Tien , Nan Duan , Furu Wei

Scripting interfaces enable users to automate tasks and customize software workflows, but creating scripts traditionally requires programming expertise and familiarity with specific APIs, posing barriers for many users. While Large Language…

人工智能 · 计算机科学 2026-02-09 Paiheng Xu , Gang Wu , Xiang Chen , Tong Yu , Chang Xiao , Franck Dernoncourt , Tianyi Zhou , Wei Ai , Viswanathan Swaminathan

Information graphics are pivotal in effective information dissemination and storytelling. However, creating such graphics is extremely challenging for non-professionals, since the design process requires multifaceted skills and…

人机交互 · 计算机科学 2024-01-25 Qirui Huang , Min Lu , Joel Lanir , Dani Lischinski , Daniel Cohen-Or , Hui Huang

Large language models appear quite creative, often performing on par with the average human on creative tasks. However, research on LLM creativity has focused solely on \textit{products}, with little attention on the creative…

人机交互 · 计算机科学 2024-06-07 Surabhi S. Nath , Peter Dayan , Claire Stevenson

Design space exploration (DSE) for Text-to-Image (TTI) models entails navigating a vast, opaque space of possible image outputs, through a commensurately vast input space of hyperparameters and prompt text. Minor adjustments to prompt input…

Prompt engineering is a new paradigm for enhancing the performance of trained neural network models. For optimizing text-style prompts, existing methods usually individually operate small portions of a text step by step, which either breaks…

计算与语言 · 计算机科学 2023-10-03 Yujian Betterest Li , Kai Wu

This paper introduces WordArt Designer, a user-driven framework for artistic typography synthesis, relying on the Large Language Model (LLM). The system incorporates four key modules: the LLM Engine, SemTypo, StyTypo, and TexTypo modules.…

Generative AI models offer many possibilities for text creation and transformation. Current graphical user interfaces (GUIs) for prompting them lack support for iterative exploration, as they do not represent prompts as actionable interface…

人机交互 · 计算机科学 2025-03-28 Rifat Mehreen Amin , Oliver Hans Kühle , Daniel Buschek , Andreas Butz

This paper assesses the potential for large language models (LLMs) to serve as assistive tools in the creative writing process, by means of a single, in-depth case study. In the course of the study, we develop interactive and multi-voice…

计算与语言 · 计算机科学 2023-12-08 Murray Shanahan , Catherine Clarke

Inspirational search, the process of exploring designs to inform and inspire new creative work, is pivotal in mobile user interface (UI) design. However, exploring the vast space of UI references remains a challenge. Existing AI-based UI…

人机交互 · 计算机科学 2025-02-18 Seokhyeon Park , Yumin Song , Soohyun Lee , Jaeyoung Kim , Jinwook Seo

Therapeutic art activities, such as expressive drawing and painting, require the synergy between creative visual production and interactive dialogue. Recent advancements in Multimodal Large Language Models (MLLMs) have expanded the capacity…

人机交互 · 计算机科学 2026-05-12 Le Lin , Zihao Zhu , Rainbow Tin Hung Ho , Jing Liao , Yuhan Luo

Node-based programming languages are increasingly popular in media arts coding domains. These languages are designed to be accessible to users with limited coding experience, allowing them to achieve creative output without an extensive…

We propose a novel architecture for integrating large language models (LLMs) with a persistent, interactive Lisp environment. This setup enables LLMs to define, invoke, and evolve their own tools through programmatic interaction with a live…

编程语言 · 计算机科学 2025-06-13 Jordi de la Torre

Domain experts increasingly use automated data science tools to incorporate machine learning (ML) models in their work but struggle to "debug" these models when they are incorrect. For these experts, semantic interactions can provide an…

人机交互 · 计算机科学 2023-10-17 Anamaria Crisan , Maddie Shang , Eric Brochu

Prompt-learning has become a new paradigm in modern natural language processing, which directly adapts pre-trained language models (PLMs) to $cloze$-style prediction, autoregressive modeling, or sequence to sequence generation, resulting in…

计算与语言 · 计算机科学 2021-11-04 Ning Ding , Shengding Hu , Weilin Zhao , Yulin Chen , Zhiyuan Liu , Hai-Tao Zheng , Maosong Sun

Interactive spatial layouts empower users to synthesize information and organize findings for sensemaking. While Large Language Models (LLMs) can automate narrative generation from spatial layouts, current collage-based and re-generation…

人机交互 · 计算机科学 2026-04-23 Xuxin Tang , Ibrahim Tahmid , Eric Krokos , Kirsten Whitley , Xuan Wang , Chris North

The rise of large language models (LLMs) has highlighted the importance of prompt engineering as a crucial technique for optimizing model outputs. While experimentation with various prompting methods, such as Few-shot, Chain-of-Thought, and…

人工智能 · 计算机科学 2026-03-27 Michael Hewing , Vincent Leinhos

Explorative flow visualization allows domain experts to analyze complex flow structures by interactively investigating flow patterns. However, traditional visual interfaces often rely on specialized graphical representations and…

人机交互 · 计算机科学 2025-08-11 Weihan Zhang , Jun Tao

Large language models (LLMs) have shown great potential in automating significant aspects of coding by producing natural code from informal natural language (NL) intent. However, given NL is informal, it does not lend easily to checking…

软件工程 · 计算机科学 2024-10-04 Sarah Fakhoury , Aaditya Naik , Georgios Sakkas , Saikat Chakraborty , Shuvendu K. Lahiri