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Damien Masson

Publications and source records attributed to Damien Masson.

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AInimation: Animating from Prompt to AI-Generated Responses

We explore the use of animated transitions between a prompt and an AI-generated response. After reviewing 800 examples of prompts and responses, we devise a taxonomy of animated transitions for multimodal text- and image-generative models. The proposed animations include translating and morphing elements of the prompt to their final location in the response; highlighting modifications such as fixed typos; overlaying structural requirements to verify them; and displaying how a model understands references. A study shows that adding animated transitions helps users review the response: participants performed 43% better at locating elements in the response; 153% better at identifying changes; and 20% better at verifying the prompt was correctly interpreted. Our work applies to all software that integrates AI and shows that well-crafted, slower animations are preferable to instant AI responses.

cs.HC

How Notations Evolve: A Historical Analysis with Implications for Supporting User-Defined Abstractions

Traditional human-computer interaction takes place through formally-specified systems like structured UIs and programming languages. Recent AI systems promise a new set of informal interactions with computers through natural language and other notational forms. These informal interactions can then lead to formal representations, but depend upon pre-existing formalisms known to both humans and AI. What about novel formalisms and notations? How are new abstractions created, evolved, and incrementally formalized over time -- and how might new systems, in turn, be explicitly designed to support these processes? We conduct a comparative historical analysis of notation development to identify some relevant characteristics. These include three social stages of notation development: invention & incubation, dispersion & divergence, and institutionalization & sanctification, as well as three functional stages: descriptive, generative, and evaluative. Within and across these stages, we detail several patterns, such as the role of linking and grounding metaphors, dimensions of meaningful variation, and analogical alignment. Finally, we offer some implications for design.

cs.HC

Visual Story-Writing: Writing by Manipulating Visual Representations of Stories

We define "visual story-writing" as using visual representations of story elements to support writing and revising narrative texts. To demonstrate this approach, we developed a text editor that automatically visualizes a graph of entity interactions, movement between locations, and a timeline of story events. Interacting with these visualizations results in suggested text edits: for example, connecting two characters in the graph creates an interaction between them, moving an entity updates their described location, and rearranging events on the timeline reorganizes the narrative sequence. Through two user studies on narrative text editing and writing, we found that visuals supported participants in planning high-level revisions, tracking story elements, and exploring story variations in ways that encourage creativity. Broadly, our work lays the foundation for writing support, not just through words, but also visuals.

cs.HC

Making the Write Connections: Linking Writing Support Tools with Writer's Needs

This work sheds light on whether and how creative writers' needs are met by existing research and commercial writing support tools (WST). We conducted a need finding study to gain insight into the writers' process during creative writing through a qualitative analysis of the response from an online questionnaire and Reddit discussions on r/Writing. Using a systematic analysis of 115 tools and 67 research papers, we map out the landscape of how digital tools facilitate the writing process. Our triangulation of data reveals that research predominantly focuses on the writing activity and overlooks pre-writing activities and the importance of visualization. We distill 10 key takeaways to inform future research on WST and point to opportunities surrounding underexplored areas. Our work offers a holistic and up-to-date account of how tools have transformed the writing process, guiding the design of future tools that address writers' evolving and unmet needs.

cs.HC

DuSK: Faster Indirect Text Entry Supporting Out-Of-Vocabulary Words for Touchpads

Given the ubiquity of SmartTVs and head-mounted-display-based virtual environments, recent research has explored techniques to support eyes-free text entry using touchscreen devices. However, proposed techniques, leveraging lexicons, limit the user's ability to enter out-of-vocabulary words. In this paper, we investigate how to enter text while relying on unambiguous input to support out-of-vocabulary words. Through an iterative design approach, and after a careful investigation of actions that can be accurately and rapidly performed eyes-free, we devise DuSK, a {Du}al-handed, {S}troke-based, 1{K}eyboarding technique. In a controlled experiment, we show initial speeds of 10 WPM steadily increasing to 13~WPM with training. DuSK outperforms the common cursor-based text entry technique widely deployed in commercial SmartTVs (8 WPM) and is comparable to other eyes-free lexicon-based techniques, but with the added benefit of supporting out-of-vocabulary word input.

cs.HC

Textoshop: Interactions Inspired by Drawing Software to Facilitate Text Editing

We explore how interactions inspired by drawing software can help edit text. Making an analogy between visual and text editing, we consider words as pixels, sentences as regions, and tones as colours. For instance, direct manipulations move, shorten, expand, and reorder text; tools change number, tense, and grammar; colours map to tones explored along three dimensions in a tone picker; and layers help organize and version text. This analogy also leads to new workflows, such as boolean operations on text fragments to construct more elaborated text. A study shows participants were more successful at editing text and preferred using the proposed interface over existing solutions. Broadly, our work highlights the potential of interaction analogies to rethink existing workflows, while capitalizing on familiar features.

cs.HC

DirectGPT: A Direct Manipulation Interface to Interact with Large Language Models

We characterize and demonstrate how the principles of direct manipulation can improve interaction with large language models. This includes: continuous representation of generated objects of interest; reuse of prompt syntax in a toolbar of commands; manipulable outputs to compose or control the effect of prompts; and undo mechanisms. This idea is exemplified in DirectGPT, a user interface layer on top of ChatGPT that works by transforming direct manipulation actions to engineered prompts. A study shows participants were 50% faster and relied on 50% fewer and 72% shorter prompts to edit text, code, and vector images compared to baseline ChatGPT. Our work contributes a validated approach to integrate LLMs into traditional software using direct manipulation. Data, code, and demo available at https://osf.io/3wt6s.

cs.HC