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PriorWeaver: Prior Elicitation via Iterative Dataset Construction

In Bayesian analysis, prior elicitation, or the process of facilitating the expression of one’s beliefs to inform statistical modeling, is an essential yet challenging step. Analysts often have beliefs about real-world variables and their relationships. However, existing tools require analysts to translate these belie…

Yuwei Xiao et al.University of California Los Angeles

Flowco: Mixed-Initiative Authoring of Reliable End-to-End Data Analyses via Dataflow Graphs and LLMs

Conducting data analysis typically involves authoring code to trans- form, visualize, analyze, and interpret data. Large Language Models (LLMs) are now capable of generating such code for simple, routine analyses, and they have the potential to democratize data science by enabling those with limited programming expert…

Stephen Freund et al.Williams College

Dreamcrafter: Immersive Editing of 3D Radiance Fields Through Flexible, Generative Inputs and Outputs

Authoring 3D scenes is a central task for spatial computing applications. Competing visions for lowering existing barriers are (1) focus on immersive, direct manipulation of 3D content or (2) leverage AI techniques that capture real scenes (3D Radiance Fields such as, NeRFs, 3D Gaussian Splatting) and modify them at a…

Cyrus Vachha et al.University of California

Beyond Code Generation: LLM-supported Exploration of the Program Design Space

In this work, we explore explicit Large Language Model (LLM)-powered support for the iterative design of computer programs. Program design, like other design activity, is characterized by navigating a space of alternative problem formulations and associated solutions in an iterative fashion. LLMs are potentially power…

J.D. Zamfirescu-Pereira et al.University of California - Berkeley

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rTisane: Externalizing conceptual models for data analysis increases engagement with domain knowledge and improves statistical model quality

Statistical models should accurately reflect analysts’ domain knowledge about variables and their relationships. While recent tools let analysts express these assumptions and use them to produce a resulting statistical model, it remains unclear what analysts want to express and how externalization impacts statistical…

Eunice Jun et al.University of California Los Angeles

Odyssey: An Interactive Workbench for Expert-Driven Floating-Point Expression Rewriting

In recent years, researchers have proposed a number of automated tools to identify and improve floating-point rounding error in math- ematical expressions. However, users struggle to effectively apply these tools. In this paper, we work with novices, experts, and tool developers to investigate user needs during the ex…

Edward Misback et al.University Of Washington

Understanding and Supporting Debugging Workflows in Multiverse Analysis

Multiverse analysis—a paradigm for statistical analysis that considers all combinations of reasonable analysis choices in parallel—promises to improve transparency and reproducibility. Although recent tools help analysts specify multiverse analyses, they remain difficult to use in practice. In this work, we identify d…

Ken Gu et al.University Of Washington

Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships

Proper statistical modeling incorporates domain theory about how concepts relate and details of how data were measured. However, data analysts currently lack tool support for recording and reasoning about domain assumptions, data collection, and modeling choices in an integrated manner, leading to mistakes that can co…

Eunice Jun et al.University of California Los Angeles

Tea: A High-level Language and Runtime System for Automating Statistical Analysis

Though statistical analyses are centered on research questions and hypotheses, current statistical analysis tools are not. Users must first translate their hypotheses into specific statistical tests and then perform API calls with functions and parameters. To do so accurately requires that users have statistical exper…

Eunice Jun et al.University of California Los Angeles

Circadian Rhythms and Physiological Synchrony: Evidence of the Impact of Diversity on Small Group Creativity

Circadian rhythms determine daily sleep cycles, mood, and cognition. Depending on an individual's circadian preference, or chronotype (i.e.,``early birds'' and ``night owls''), the rhythms shift earlier or later in the day. Early birds experience circadian arousal peaks earlier in the morning than night owls. Prior wo…

Eunice Jun et al.University of California Los Angeles

Groups and creativity

Types of Motivation Affect Study Selection, Attention, and Dropouts in Online Experiments

Understanding whether and how motivation affects participation in online experiments is critical because who contributes and how they contribute can affect the validity of findings. Analyzing data from 7,674 participants across three different studies on the volunteer-based online experiment platform LabintheWild, we…

Eunice Jun et al.University of California Los Angeles

Motivation in Online Collaboration

Digestif: Promoting Science Communication in Online Experiments

Online experiments allow researchers to collect data from large, demographically diverse global populations. Unlike in-lab studies, however, online experiments often fail to inform participants about the research to which they contribute. This paper is the first to investigate barriers that prevent researchers from pr…

Eunice Jun et al.University of California Los Angeles

Research Methods

Paper Title	Authors	Research Topics
PriorWeaver: Prior Elicitation via Iterative Dataset Construction In Bayesian analysis, prior elicitation, or the process of facilitating the expression of one’s beliefs to inform statistical modeling, is an essential yet challenging step. Analysts often have beliefs about real-world variables and their relationships. However, existing tools require analysts to translate these belie…	YX Yuwei Xiao et al.University of California Los Angeles
Flowco: Mixed-Initiative Authoring of Reliable End-to-End Data Analyses via Dataflow Graphs and LLMs Conducting data analysis typically involves authoring code to trans- form, visualize, analyze, and interpret data. Large Language Models (LLMs) are now capable of generating such code for simple, routine analyses, and they have the potential to democratize data science by enabling those with limited programming expert…	SF Stephen Freund et al.Williams College
Dreamcrafter: Immersive Editing of 3D Radiance Fields Through Flexible, Generative Inputs and Outputs Authoring 3D scenes is a central task for spatial computing applications. Competing visions for lowering existing barriers are (1) focus on immersive, direct manipulation of 3D content or (2) leverage AI techniques that capture real scenes (3D Radiance Fields such as, NeRFs, 3D Gaussian Splatting) and modify them at a…	CV Cyrus Vachha et al.University of California
emoji_events Beyond Code Generation: LLM-supported Exploration of the Program Design Space In this work, we explore explicit Large Language Model (LLM)-powered support for the iterative design of computer programs. Program design, like other design activity, is characterized by navigating a space of alternative problem formulations and associated solutions in an iterative fashion. LLMs are potentially power…	JZ J.D. Zamfirescu-Pereira et al.University of California - Berkeley
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
emoji_events rTisane: Externalizing conceptual models for data analysis increases engagement with domain knowledge and improves statistical model quality Statistical models should accurately reflect analysts’ domain knowledge about variables and their relationships. While recent tools let analysts express these assumptions and use them to produce a resulting statistical model, it remains unclear what analysts want to express and how externalization impacts statistical…	EJ Eunice Jun et al.University of California Los Angeles
Odyssey: An Interactive Workbench for Expert-Driven Floating-Point Expression Rewriting In recent years, researchers have proposed a number of automated tools to identify and improve floating-point rounding error in math- ematical expressions. However, users struggle to effectively apply these tools. In this paper, we work with novices, experts, and tool developers to investigate user needs during the ex…	EM Edward Misback et al.University Of Washington
Understanding and Supporting Debugging Workflows in Multiverse Analysis Multiverse analysis—a paradigm for statistical analysis that considers all combinations of reasonable analysis choices in parallel—promises to improve transparency and reproducibility. Although recent tools help analysts specify multiverse analyses, they remain difficult to use in practice. In this work, we identify d…	KG Ken Gu et al.University Of Washington
emoji_events Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships Proper statistical modeling incorporates domain theory about how concepts relate and details of how data were measured. However, data analysts currently lack tool support for recording and reasoning about domain assumptions, data collection, and modeling choices in an integrated manner, leading to mistakes that can co…	EJ Eunice Jun et al.University of California Los Angeles
Tea: A High-level Language and Runtime System for Automating Statistical Analysis Though statistical analyses are centered on research questions and hypotheses, current statistical analysis tools are not. Users must first translate their hypotheses into specific statistical tests and then perform API calls with functions and parameters. To do so accurately requires that users have statistical exper…	EJ Eunice Jun et al.University of California Los Angeles
Circadian Rhythms and Physiological Synchrony: Evidence of the Impact of Diversity on Small Group Creativity Circadian rhythms determine daily sleep cycles, mood, and cognition. Depending on an individual's circadian preference, or chronotype (i.e.,``early birds'' and ``night owls''), the rhythms shift earlier or later in the day. Early birds experience circadian arousal peaks earlier in the morning than night owls. Prior wo…	EJ Eunice Jun et al.University of California Los Angeles	Groups and creativity
Types of Motivation Affect Study Selection, Attention, and Dropouts in Online Experiments Understanding whether and how motivation affects participation in online experiments is critical because who contributes and how they contribute can affect the validity of findings. Analyzing data from 7,674 participants across three different studies on the volunteer-based online experiment platform LabintheWild, we…	EJ Eunice Jun et al.University of California Los Angeles	Motivation in Online Collaboration
Digestif: Promoting Science Communication in Online Experiments Online experiments allow researchers to collect data from large, demographically diverse global populations. Unlike in-lab studies, however, online experiments often fail to inform participants about the research to which they contribute. This paper is the first to investigate barriers that prevent researchers from pr…	EJ Eunice Jun et al.University of California Los Angeles	Research Methods