111 citations · 448 across the 41 of their papers we have counts for
44 papers
Live Artifacts: Authoring Dynamic Media via Live Layers Encapsulating Generative Specifications
Leixian Shen, Haotian Li, Hugo Romat +3
We frame Live Artifacts as a class of persistent generative media between static assets and interactive software. Unlike conventional generative outputs that collapse into static f…
Informal Learning Emerges in Everyday Human-LLM Interaction
Zixin Chen, Haotian Li, Ziang Xiao +2
As LLMs become increasingly capable of completing tasks for users, a central concern is that everyday AI use may become primarily cognitive offloading, eroding the opportunities th…
Multi-agent AI systems outperform human teams in creativity
Tiancheng Hu, Yixuan Jiang, Haotian Li +5
Although artificial intelligence (AI) now matches or exceeds human performance across numerous cognitive tasks, creativity remains a highly contested frontier. As AI systems based…
Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations
Nanxu Gong, Zixin Chen, Haotian Li +5
Improving the Theory of Mind (ToM) capability of Large Language Models (LLMs) is crucial for effective social interactions between these AI models and humans. However, the existing…
Social-R1: Towards Human-like Social Reasoning in LLMs
Jincenzi Wu, Yuxuan Lei, Jianxun Lian +5
While large language models demonstrate remarkable capabilities across numerous domains, social intelligence - the capacity to perceive social cues, infer mental states, and genera…
From Passive Consumption to Active Interaction: Exploring Interactive LLM Scaffolding to Support Learning Engagement
Zixin Chen, Haotian Li, Zhe Liu +2
Large Language Models (LLMs) are increasingly used as learning companions, providing scaffolded explanations, hints, or step-by-step guidance. However, in current LLM-based learnin…
To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks
Nanxu Gong, Haotian Li, Sixun Dong +3
Theory of Mind (ToM) assesses whether models can infer hidden mental states such as beliefs, desires, and intentions, which is essential for natural social interaction. Although re…
StoryLensEdu: Personalized Learning Report Generation through Narrative-Driven Multi-Agent Systems
Leixian Shen, Yan Luo, Rui Sheng +4
Personalized feedback plays an important role in self-regulated learning (SRL), helping students track progress and refine their strategies. However, current common solutions, such…
How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of Screenwriters
Yuying Tang, Jiayi Zhou, Haotian Li +3
Generative AI has greatly transformed creative work in various domains, such as screenwriting. To understand this transformation, prior research often focused on capturing a snapsh…
DuoDrama: Supporting Screenplay Refinement Through LLM-Assisted Human Reflection
Yuying Tang, Xinyi Chen, Haotian Li +3
AI has been increasingly integrated into screenwriting practice. In refinement, screenwriters expect AI to provide feedback that supports reflection across the internal perspective…
Interaction-Augmented Instruction: Modeling the Synergy of Prompts and Interactions in Human-GenAI Collaboration
Leixian Shen, Yifang Wang, Huamin Qu +2
Text prompt is the most common way for human-generative AI (GenAI) communication. Though convenient, it is challenging to convey fine-grained and referential intent. One promising…
How Does Empirical Research Facilitate Creation Tool Design? A Data Video Perspective
Leixian Shen, Leni Yang, Haotian Li +3
Empirical research in creative design deepens our theoretical understanding of design principles and perceptual effects, offering valuable guidance for innovating creation tools. H…
Prompting Generative AI with Interaction-Augmented Instructions
Leixian Shen, Haotian Li, Yifang Wang +2
The emergence of generative AI (GenAI) models, including large language models and text-to-image models, has significantly advanced the synergy between humans and AI with not only…
Xavier: Toward Better Coding Assistance in Authoring Tabular Data Wrangling Scripts
Yunfan Zhou, Xiwen Cai, Qiming Shi +5
Data analysts frequently employ code completion tools in writing custom scripts to tackle complex tabular data wrangling tasks. However, existing tools do not sufficiently link the…
Reflection on Data Storytelling Tools in the Generative AI Era from the Human-AI Collaboration Perspective
Haotian Li, Yun Wang, Huamin Qu
Human-AI collaborative tools attract attentions from the data storytelling community to lower the expertise barrier and streamline the workflow. The recent advance in large-scale g…
Understanding Screenwriters' Practices, Attitudes, and Future Expectations in Human-AI Co-Creation
Yuying Tang, Haotian Li, Minghe Lan +2
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 essen…
InterLink: Linking Text with Code and Output in Computational Notebooks
Yanna Lin, Leni Yang, Haotian Li +2
Computational notebooks, widely used for ad-hoc analysis and often shared with others, can be difficult to understand because the standard linear layout is not optimized for readin…
Reflecting on Design Paradigms of Animated Data Video Tools
Leixian Shen, Haotian Li, Yun Wang +1
Animated data videos have gained significant popularity in recent years. However, authoring data videos remains challenging due to the complexity of creating and coordinating diver…
Composing Data Stories with Meta Relations
Haotian Li, Lu Ying, Leixian Shen +3
To facilitate the creation of compelling and engaging data stories, AI-powered tools have been introduced to automate the three stages in the workflow: analyzing data, organizing f…
Constraint representation towards precise data-driven storytelling
Yu-Zhe Shi, Haotian Li, Lecheng Ruan +1
Data-driven storytelling serves as a crucial bridge for communicating ideas in a persuasive way. However, the manual creation of data stories is a multifaceted, labor-intensive, an…
Data Playwright: Authoring Data Videos with Annotated Narration
Leixian Shen, Haotian Li, Yun Wang +3
Creating data videos that effectively narrate stories with animated visuals requires substantial effort and expertise. A promising research trend is leveraging the easy-to-use natu…
Narrative Player: Reviving Data Narratives with Visuals
Zekai Shao, Leixian Shen, Haotian Li +4
Data-rich documents are commonly found across various fields such as business, finance, and science. However, a general limitation of these documents for reading is their reliance…
From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems
Leixian Shen, Haotian Li, Yun Wang +1
Creating data stories from raw data is challenging due to humans' limited attention spans and the need for specialized skills. Recent advancements in large language models (LLMs) o…
JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets
Zhihua Jin, Shiyi Liu, Haotian Li +2
Large Language Models (LLMs) have gained significant attention but also raised concerns due to the risk of misuse. Jailbreak prompts, a popular type of adversarial attack towards L…