PersonaMail: Learning and Adapting Personal Communication Preferences for Context-Aware Email Writing

Fuente: arXiv
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Hauptverfasser: Yao, Rui, Ren, Qiuyuan, Tan, Felicia Fang-Yi, Yang, Chen, Zhang, Xiaoyu, Zhao, Shengdong
Format: Preprint
Veröffentlicht: 2026
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author Yao, Rui
Ren, Qiuyuan
Tan, Felicia Fang-Yi
Yang, Chen
Zhang, Xiaoyu
Zhao, Shengdong
author_facet Yao, Rui
Ren, Qiuyuan
Tan, Felicia Fang-Yi
Yang, Chen
Zhang, Xiaoyu
Zhao, Shengdong
contents LLM-assisted writing has seen rapid adoption in interpersonal communication, yet current systems often fail to capture the subtle tones essential for effectiveness. Email writing exemplifies this challenge: effective messages require careful alignment with intent, relationship, and context beyond mere fluency. Through formative studies, we identified three key challenges: articulating nuanced communicative intent, making modifications at multiple levels of granularity, and reusing effective tone strategies across messages. We developed PersonaMail, a system that addresses these gaps through structured communication factor exploration, granular editing controls, and adaptive reuse of successful strategies. Our evaluation compared PersonaMail against standard LLM interfaces, and showed improved efficiency in both immediate and repeated use, alongside higher user satisfaction. We contribute design implications for AI-assisted communication systems that prioritize interpersonal nuance over generic text generation.
format Preprint
id arxiv_https___arxiv_org_abs_2602_17340
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle PersonaMail: Learning and Adapting Personal Communication Preferences for Context-Aware Email Writing
Yao, Rui
Ren, Qiuyuan
Tan, Felicia Fang-Yi
Yang, Chen
Zhang, Xiaoyu
Zhao, Shengdong
Human-Computer Interaction
LLM-assisted writing has seen rapid adoption in interpersonal communication, yet current systems often fail to capture the subtle tones essential for effectiveness. Email writing exemplifies this challenge: effective messages require careful alignment with intent, relationship, and context beyond mere fluency. Through formative studies, we identified three key challenges: articulating nuanced communicative intent, making modifications at multiple levels of granularity, and reusing effective tone strategies across messages. We developed PersonaMail, a system that addresses these gaps through structured communication factor exploration, granular editing controls, and adaptive reuse of successful strategies. Our evaluation compared PersonaMail against standard LLM interfaces, and showed improved efficiency in both immediate and repeated use, alongside higher user satisfaction. We contribute design implications for AI-assisted communication systems that prioritize interpersonal nuance over generic text generation.
title PersonaMail: Learning and Adapting Personal Communication Preferences for Context-Aware Email Writing
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.17340