LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexia

Goodman, Steven; Buehler, Erin; Clary, Patrick; Coenen, Andy; Donsbach, Aaron; Horne, Tiffanie; Lahav, Michal; Macdonald, Robert D.; Michaels, Rain; Narayanan, Ajit; Pushkarna, Mahima; Riley, Joel S.; Santana, Alex Fabiano Bertollo; Lei, Shi,; Sweeney, Rachel; Weaver, Phil; Yuan, Ann; Morris, Meredith Ringel

doi:10.1145/3517428.3544819

Cited by 30 publications

(8 citation statements)

References 44 publications

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“…Both of them facilitate the information-seeking process. Other works focus on designing interfaces for specific writing tasks, such as email writing [10], story creation [46], argumentative writing [47], scientific writing [8] and journalistic angle ideation [33]. These interfaces ensure users achieve ideal results through iterative interactions.…”

Section: Visual Interfaces For Llmsmentioning

confidence: 99%

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke

Liu

Chen

Zhang

et al. 2021

J. Zhejiang Univ. Sci. B

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This study aimed to uncover underlying mechanisms and promising intervention targets of heart failure (HF)-related stroke. HF-related dataset GSE42955 and stroke-related dataset GSE58294 were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub genes. Gene Ontology (GO) and pathway enrichment analyses were performed on genes in the key modules. Genes in HF-and stroke-related key modules were intersected to obtain common genes for HF-related stroke, which were further intersected with hub genes of stroke-related key modules to obtain key genes in HF-related stroke. Key genes were functionally annotated through GO in the Reactome and Cytoscape databases. Finally, key genes were validated in these two datasets and other datasets. HF-and stroke-related datasets each identified two key modules. Functional enrichment analysis indicated that protein ubiquitination, Wnt signaling, and exosomes were involved in both HF-and stroke-related key modules. Additionally, ten hub genes were identified in stroke-related key modules and 155 genes were identified as common genes in HF-related stroke. OTU deubiquitinase with linear linkage specificity (OTULIN) and nuclear factor interleukin 3-regulated (NFIL3) were determined to be the key genes in HF-related stroke. Through functional annotation, OTULIN was involved in protein ubiquitination and Wnt signaling, and NFIL3 was involved in DNA binding and transcription. Importantly, OTULIN and NFIL3 were also validated to be differentially expressed in all HF and stroke groups. Protein ubiquitination, Wnt signaling, and exosomes were involved in HF-related stroke. OTULIN and NFIL3 may play a key role in HF-related stroke through regulating these processes, and thus serve as promising intervention targets.

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Section: Visual Interfaces For Llmsmentioning

confidence: 99%

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke

Liu

Chen

Zhang

et al. 2021

J. Zhejiang Univ. Sci. B

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“…While some researchers imagine its contributions as a design space, material, and avenue of prototyping for human-centered computing systems [68], a lot of attention has been devoted to how its changing the landscape of learning and educational systems [42]. Others have suggested its potential for supporting communication for people with disabilities, such as enhancing experiences for AAC users [87], writing AI-assisted emails for adults with dyslexia [28] and even speech-language pathologists in delivering therapy to autistic individuals in clinical settings [20].…”

Section: Autism Generative Ai and Llmsmentioning

confidence: 99%

“It’s the only thing I can trust”: Envisioning Large Language Model Use by Autistic Workers for Communication Assistance

Jang,

Moharana,

Carrington

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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“…. Single text suggestions can be shown inline [4,8,17,48], whereas multiple suggestions are shown as popup lists of about three to six entries [6,26]. Beyond that, Singh et al [41] evaluated how writers use suggestions displayed as images and sound.…”

Section: Display Of Suggestionsmentioning

confidence: 99%

“…Related work showed suggestions automatically after short inactivity [4,6] or gated by a utility function [24]. Alternatively, recent work has also explored designs in which users explicitly request suggestions with a hotkey [7,17,26,41,48]. We also use this design with an explicit request key to better understand how and when users request suggestions.…”

Section: Implicit Vs Explicit Triggermentioning

confidence: 99%

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Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting

Hai

Goller

Lehmann

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexia

Cited by 30 publications

References 44 publications

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke

“It’s the only thing I can trust”: Envisioning Large Language Model Use by Autistic Workers for Communication Assistance

Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting

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