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Jeffrey Mu

dblp:430/4696 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0009-8925-8596ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › computer-supported cooperative work › collaborative applications
collaborative physical tasks
1.012026
Gesturing Toward Abstraction: Multimodal Convention Formation in Collaborative Physical Tasks · CHI 2026
Collaborative and social computing › mixed reality collaboration
collaborative augmented reality
0.312026
Gesturing Toward Abstraction: Multimodal Convention Formation in Collaborative Physical Tasks · CHI 2026

Methods — techniques the papers use, named apart from their topics

probabilistic modeling · 1.0online study · 1.0lab study · 1.0
YearPublicationVenuePosition
2026 Gesturing Toward Abstraction: Multimodal Convention Formation in Collaborative Physical Tasks
abstract
A quintessential feature of human intelligence is the ability to create ad hoc conventions over time to achieve shared goals efficiently. We investigate how communication strategies evolve through repeated collaboration as people coordinate on shared procedural abstractions. To this end, we conducted an online unimodal study (n = 98) using natural language to probe abstraction hierarchies. In a follow-up lab study (n = 40), we examined how multimodal communication (speech and gestures) changed during physical collaboration. Pairs used augmented reality to isolate their partner’s hand and voice; one participant viewed a 3D virtual tower and sent instructions to the other, who built the physical tower. Participants became faster and more accurate by establishing linguistic and gestural abstractions and using cross-modal redundancy to emphasize key changes from previous interactions. Based on these findings, we extend probabilistic models of convention formation to multimodal settings, capturing shifts in modality preferences. Our findings and model provide building blocks for designing convention-aware intelligent agents situated in the physical world.
Kiyosu Maeda, William P. McCarthy, Ching-Yi Tsai, Jeffrey Mu, Robert D. Hawkins, Judith E. Fan, Parastoo Abtahi
CHI4