arXiv subjects

Yuying Tang

Publications and source records attributed to Yuying Tang.

8 recordsLinked to original sources

arXiv2026

How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of Screenwriters

Generative AI has greatly transformed creative work in various domains, such as screenwriting. To understand this transformation, prior research often focused on capturing a snapshot of human-AI co-creation practice at a specific moment, with less attention to how humans mobilize, regulate, and reflect to form the practice gradually. Motivated by Bandura's theory of human agency, we conducted a two-week study with 19 professional screenwriters to investigate how they embraced AI in their creation process. Our findings revealed that screenwriters not only mindfully planned, foresaw, and responded to AI usage, but, more importantly, through reflections on practice, they developed themselves and human-AI co-creation paradigms, such as cognition, strategies, and workflows. They also expressed various expectations for how future AI should better support their agency. Based on our findings, we conclude this paper with extensive discussion and actionable suggestions to screenwriters, tool developers, and researchers for sustainable human-AI co-creation.

cs.HC↗

arXiv2026

DuoDrama: Supporting Screenplay Refinement Through LLM-Assisted Human Reflection

AI has been increasingly integrated into screenwriting practice. In refinement, screenwriters expect AI to provide feedback that supports reflection across the internal perspective of characters and the external perspective of the overall story. However, existing AI tools cannot sufficiently coordinate the two perspectives to meet screenwriters' needs. To address this gap, we present DuoDrama, an AI system that generates feedback to assist screenwriters' reflection in refinement. To enable DuoDrama, based on performance theories and a formative study with nine professional screenwriters, we design the Experience-Grounded Feedback Generation Workflow for Human Reflection (ExReflect). In ExReflect, an AI agent adopts an experience role to generate experience and then shifts to an evaluation role to generate feedback based on the experience. A study with fourteen professional screenwriters shows that DuoDrama improves feedback quality and alignment and enhances the effectiveness, depth, and richness of reflection. We conclude by discussing broader implications and future directions.

cs.HC↗

arXiv2025

PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration

Researchers frequently need to synthesize their own publications into coherent narratives that demonstrate their scholarly contributions. To suit diverse communication contexts, exploring alternative ways to organize one's work while maintaining coherence is particularly challenging, especially in interdisciplinary fields like HCI where individual researchers' publications may span diverse domains and methodologies. In this paper, we present PaperBridge, a human-AI co-exploration system informed by a formative study and content analysis. PaperBridge assists researchers in exploring diverse perspectives for organizing their publications into coherent narratives. At its core is a bi-directional analysis engine powered by large language models, supporting iterative exploration through both top-down user intent (e.g., determining organization structure) and bottom-up refinement on narrative components (e.g., thematic paper groupings). Our user study (N=12) demonstrated PaperBridge's usability and effectiveness in facilitating the exploration of alternative research narratives. Our findings also provided empirical insights into how interactive systems can scaffold academic communication tasks.

cs.HC↗

arXiv2025

Understanding Screenwriters' Practices, Attitudes, and Future Expectations in Human-AI Co-Creation

With the rise of AI technologies and their growing influence in the screenwriting field, understanding the opportunities and concerns related to AI's role in screenwriting is essential for enhancing human-AI co-creation. Through semi-structured interviews with 23 screenwriters, we explored their creative practices, attitudes, and expectations in collaborating with AI for screenwriting. Based on participants' responses, we identified the key stages in which they commonly integrated AI, including story structure & plot development, screenplay text, goal & idea generation, and dialogue. Then, we examined how different attitudes toward AI integration influence screenwriters' practices across various workflow stages and their broader impact on the industry. Additionally, we categorized their expected assistance using four distinct roles of AI: actor, audience, expert, and executor. Our findings provide insights into AI's impact on screenwriting practices and offer suggestions on how AI can benefit the future of screenwriting.

cs.HC↗

arXiv2024

What's Next? Exploring Utilization, Challenges, and Future Directions of AI-Generated Image Tools in Graphic Design

Recent advancements in artificial intelligence, such as computer vision and deep learning, have led to the emergence of numerous generative AI platforms, particularly for image generation. However, the application of AI-generated image tools in graphic design has not been extensively explored. This study conducted semi-structured interviews with seven designers of varying experience levels to understand their current usage, challenges, and future functional needs for AI-generated image tools in graphic design. As our findings suggest, AI tools serve as creative partners in design, enhancing human creativity, offering strategic insights, and fostering team collaboration and communication. The findings provide guiding recommendations for the future development of AI-generated image tools, aimed at helping engineers optimize these tools to better meet the needs of graphic designers.

cs.HC↗

arXiv2024

Exploring the Impact of AI-generated Image Tools on Professional and Non-professional Users in the Art and Design Fields

The rapid proliferation of AI-generated image tools is transforming the art and design fields, challenging traditional notions of creativity and impacting both professional and non-professional users. For the purposes of this paper, we define 'professional users' as individuals who self-identified in our survey as 'artists,' 'designers,' 'filmmakers,' or 'art and design students,' and 'non-professional users' as individuals who self-identified as 'others.' This study explores how AI-generated image tools influence these different user groups. Through an online survey (N=380) comprising 173 professional users and 207 non-professional users, we examine differences in the utilization of AI tools, user satisfaction and challenges, applications in creative processes, perceptions and impacts, and acceptance levels. Our findings indicate persistent concerns about image quality, cost, and copyright issues. Additionally, the usage patterns of non-professional users suggest that AI tools have the potential to democratize creative processes, making art and design tasks more accessible to individuals without traditional expertise. This study provides insights into the needs of different user groups and offers recommendations for developing more user-centered AI tools, contributing to the broader discussion on the future of AI in the art and design fields.

cs.HC↗

arXiv2023

AI Nushu: An Exploration of Language Emergence in Sisterhood -Through the Lens of Computational Linguistics

This paper presents "AI Nushu," an emerging language system inspired by Nushu (women's scripts), the unique language created and used exclusively by ancient Chinese women who were thought to be illiterate under a patriarchal society. In this interactive installation, two artificial intelligence (AI) agents are trained in the Chinese dictionary and the Nushu corpus. By continually observing their environment and communicating, these agents collaborate towards creating a standard writing system to encode Chinese. It offers an artistic interpretation of the creation of a non-western script from a computational linguistics perspective, integrating AI technology with Chinese cultural heritage and a feminist viewpoint.

cs.CL↗

arXiv2023

Decentralized Governance for Virtual Community(DeGov4VC): Optimal Policy Design of Human-plant Symbiosis Co-creation

Does the decentralized nature of user behavior in interactive virtual communities help create rules promoting user engagement? Through scenarios like planting, this framework suggests a new paradigm for mutual influence that allows users to impact communities' political decisions. Sixteen participants in the first round of interviews were involved in the framework's creation. Then we developed and implemented our framework in the community with the help of other stakeholders. This proof-of-concept creates user groups using information from users' daily activities as input and grows the green plants in a virtual environment. Finally, we involved AI agents and stakeholders in the framework test and iterations. Our study's user evaluation of a few key stakeholders demonstrates how our strategy enhances user viscosity and experience. Via human-planting ecosystems in a virtual community, this research gives a fresh viewpoint on decentralized governance and an engaging method for co-creating interactive ecological communities.

cs.HC↗