arXiv subjects

Scott Carter

Publications and source records attributed to Scott Carter.

13 recordsLinked to original sources

arXiv2026

Generating Place-Based Compromises Between Two Points of View

Large Language Models (LLMs) excel academically but struggle with social intelligence tasks, such as creating good compromises. In this paper, we present methods for generating empathically neutral compromises between two opposing viewpoints. We first compared four different prompt engineering methods using Claude 3 Opus and a dataset of 2,400 contrasting views on shared places. A subset of the gen erated compromises was evaluated for acceptability in a 50-participant study. We found that the best method for generating compromises between two views used external empathic similarity between a compromise and each viewpoint as iterative feedback, outperforming stan dard Chain of Thought (CoT) reasoning. The results indicate that the use of empathic neutrality improves the acceptability of compromises. The dataset of generated compromises was then used to train two smaller foundation models via margin-based alignment of human preferences, improving efficiency and removing the need for empathy estimation during inference.

cs.CL↗

arXiv2025

An Extension of Khovanov Homology to Immersed Surface Cobordisms

We show that an oriented surface in $\mathbb{R}^4$ containing double point singularities induces a map between the Khovanov homology groups of its boundary links in a functorial way. As part of this work, the movie moves of Carter and Saito are extended to surfaces with double points.

math.GT↗

arXiv2025

Trisected Rainbows and Braids

New explicit procedures for passing among triplane diagrams, braid movies, and braid charts for knotted surfaces in $\mathbb{R}^4$ are presented. To this end, rainbow diagrams, which lie between braid charts and triplanes, are introduced. Inequalities relating the braid index and the bridge index of 2-knots are obtained via these procedures. Another consequence is a 4-dimensional version of the classical result that ``the minimal number of Seifert circles equals the braid index of a link'' due to Yamada. The procedures are exemplified for the spun trefoil, the 2-twist spun trefoil, and other related examples. Of independent interest, an appendix is included that describes a procedure for drawing a triplane diagram for a satellite surface with a 2-sphere companion. Thus, larger families of surfaces for which we know specific triplane diagrams are obtained.

math.GT↗

arXiv2024

Save A Tree or 6 kg of CO2? Understanding Effective Carbon Footprint Interventions for Eco-Friendly Vehicular Choices

From ride-hailing to car rentals, consumers are often presented with eco-friendly options. Beyond highlighting a "green" vehicle and CO2 emissions, CO2 equivalencies have been designed to provide understandable amounts; we ask which equivalencies will lead to eco-friendly decisions. We conducted five ride-hailing scenario surveys where participants picked between regular and eco-friendly options, testing equivalencies, social features, and valence-based interventions. Further, we tested a car-rental embodiment to gauge how an individual (needing a car for several days) might behave versus the immediate ride-hailing context. We find that participants are more likely to choose green rides when presented with additional information about emissions; CO2 by weight was found to be the most effective. Further, we found that information framing - be it individual or collective footprint, positive or negative valence - had an impact on participants' choices. Finally, we discuss how our findings inform the design of effective interventions for reducing car-based carbon-emissions.

cs.HC↗

arXiv2023

Visual Elements and Cognitive Biases Influence Interpretations of Trends in Scatter Plots

Visualizations are common methods to convey information but also increasingly used to spread misinformation. It is therefore important to understand the factors people use to interpret visualizations. In this paper, we focus on factors that influence interpretations of scatter plots, investigating the extent to which common visual aspects of scatter plots (outliers and trend lines) and cognitive biases (people's beliefs) influence perception of correlation trends. We highlight three main findings: outliers skew trend perception but exert less influence than other points; trend lines make trends seem stronger but also mitigate the influence of some outliers; and people's beliefs have a small influence on perceptions of weak, but not strong correlations. From these results we derive guidelines for adjusting visual elements to mitigate the influence of factors that distort interpretations of scatter plots. We explore how these guidelines may generalize to other visualization types and make recommendations for future studies.

cs.HC↗

arXiv2023

Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge

A growing body of research has explored how to support humans in making better use of AI-based decision support, including via training and onboarding. Existing research has focused on decision-making tasks where it is possible to evaluate "appropriate reliance" by comparing each decision against a ground truth label that cleanly maps to both the AI's predictive target and the human decision-maker's goals. However, this assumption does not hold in many real-world settings where AI tools are deployed today (e.g., social work, criminal justice, and healthcare). In this paper, we introduce a process-oriented notion of appropriate reliance called critical use that centers the human's ability to situate AI predictions against knowledge that is uniquely available to them but unavailable to the AI model. To explore how training can support critical use, we conduct a randomized online experiment in a complex social decision-making setting: child maltreatment screening. We find that, by providing participants with accelerated, low-stakes opportunities to practice AI-assisted decision-making in this setting, novices came to exhibit patterns of disagreement with AI that resemble those of experienced workers. A qualitative examination of participants' explanations for their AI-assisted decisions revealed that they drew upon qualitative case narratives, to which the AI model did not have access, to learn when (not) to rely on AI predictions. Our findings open new questions for the study and design of training for real-world AI-assisted decision-making.

cs.HC↗

arXiv2022

Towards a Learner-Centered Explainable AI: Lessons from the learning sciences

In this short paper, we argue for a refocusing of XAI around human learning goals. Drawing upon approaches and theories from the learning sciences, we propose a framework for the learner-centered design and evaluation of XAI systems. We illustrate our framework through an ongoing case study in the context of AI-augmented social work.

cs.HC↗

arXiv2022

Understanding and Shifting Preferences for Battery Electric Vehicles

Identifying personalized interventions for an individual is an important task. Recent work has shown that interventions that do not consider the demographic background of individual consumers can, in fact, produce the reverse effect, strengthening opposition to electric vehicles. In this work, we focus on methods for personalizing interventions based on an individual's demographics to shift the preferences of consumers to be more positive towards Battery Electric Vehicles (BEVs). One of the constraints in building models to suggest interventions for shifting preferences is that each intervention can influence the effectiveness of later interventions. This, in turn, requires many subjects to evaluate effectiveness of each possible intervention. To address this, we propose to identify personalized factors influencing BEV adoption, such as barriers and motivators. We present a method for predicting these factors and show that the performance is better than always predicting the most frequent factors. We then present a Reinforcement Learning (RL) model that learns the most effective interventions, and compare the number of subjects required for each approach.

cs.IR↗

arXiv2018

Tools for online tutorials: comparing capture devices, tutorial representations, and access devices

Tutorials are one of the most fundamental means of conveying knowledge. Ideally when the task involves physical or digital objects, tutorials not only describe each step with text or via audio narration but show it as well using photos or animation. In most cases, online tutorial authors capture media from handheld mobile devices to compose these documents, but increasingly they use wearable devices as well. In this work, we explore the full life-cycle of online tutorial creation and viewing using head-mounted capture and displays. We developed a media-capture tool for Google Glass that requires minimal attention to the capture device and instead allows the author to focus on creating the tutorial's content rather than its capture. The capture tool is coupled with web-based authoring tools for creating annotatable videos and multimedia documents. In a study comparing standalone (camera on tripod) versus wearable capture (Google Glass) as well as two types of multimedia representation for authoring tutorials, we show that tutorial authors have a preference for wearable capture devices, especially when recording activities involving larger objects in non-desktop environments. Authors preferred document-based multimedia tutorials because they are more straightforward to compose and the step-based structure translates more directly to explaining a procedure. In addition, we explored using head-mounted displays for accessing tutorials in comparison to lightweight computing devices such as tablets. Our study included tutorials recorded with the same capture methods as in our access study. We found that although authors preferred head-mounted capture, tutorial consumers preferred video recorded by a camera on tripod that provides a more stable image of the workspace.

cs.HC↗

arXiv2010

mVideoCast: Mobile, real time ROI detection and streaming

A variety of applications are emerging to support streaming video from mobile devices. However, many tasks can benefit from streaming specific content rather than the full video feed which may include irrelevant, private, or distracting content. We describe a system that allows users to capture and stream targeted video content captured with a mobile device. The application incorporates a variety of automatic and interactive techniques to identify and segment desired content in the camera view, allowing the user to publish a more focused video.

cs.HC↗

arXiv2009

Beyond the Drawing Board: Toward More Effective Use of Whiteboard Content

We developed a system that augments traditional office whiteboards with computation for the purposes of retrieving, reusing, and sharing whiteboard content. Our system automatically captures changes to whiteboard images, detects significant changes, and identifies potential collaborative activities. Users then browse and search the collection of images captured from their camera or shared from other users' cameras based on aspects such as location, time, collaboration, etc. We report on the results of a formative study and on an evaluation of effectiveness of our system, and discuss additional functionality that can be built on our framework.

cs.HC↗

arXiv2009

SeeReader: An (Almost) Eyes-Free Mobile Rich Document Viewer

Reading documents on mobile devices is challenging. Not only are screens small and difficult to read, but also navigating an environment using limited visual attention can be difficult and potentially dangerous. Reading content aloud using text-tospeech (TTS) processing can mitigate these problems, but only for content that does not include rich visual information. In this paper, we introduce a new technique, SeeReader, that combines TTS with automatic content recognition and document presentation control that allows users to listen to documents while also being notified of important visual content. Together, these services allow users to read rich documents on mobile devices while maintaining awareness of their visual environment.

cs.HC↗

arXiv2009

WebNC: efficient sharing of web applications

WebNC is a system for efficiently sharing, retrieving and viewing web applications. Unlike existing screencasting and screensharing tools, WebNC is optimized to work with web pages where a lot of scrolling happens. WebNC uses a tile-based encoding to capture, transmit and deliver web applications, and relies only on dynamic HTML and JavaScript. The resulting webcasts require very little bandwidth and are viewable on any modern web browser including Firefox and Internet Explorer as well as browsers on the iPhone and Android platforms.

cs.HC↗