Demo Data from VLDB 2026 / reviewers in the wild / expert
Krystsina Shauchenka
dblp:417/5804
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0005-9175-7248ORCID · 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 · 77% Human-AI interaction · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › collaborative editing
collaborative writing |
1.0 | 1 | 2026 | Collaborative Document Editing with Multiple Users and AI Agents · CHI 2026 |
Human-AI interaction
AI-assisted writing |
0.3 | 1 | 2026 | Collaborative Document Editing with Multiple Users and AI Agents · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
user study · 1.0interaction logs · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Collaborative Document Editing with Multiple Users and AI AgentsabstractCurrent AI writing support tools are largely designed for individuals, complicating collaboration when co-writers must leave the shared workspace to use AI and then communicate and reintegrate results. We propose integrating AI agents directly into collaborative writing environments. Our prototype makes AI use visible to all users through two new shared objects: user-defined agent profiles and tasks. Agent responses appear in the familiar comment feature. In a user study (N=30), 14 teams worked on writing projects during one week. Interaction logs and interviews show that teams incorporated agents into existing norms of authorship, control, and coordination, rather than treating them as team members. Agent profiles were viewed as personal territory, while created agents and outputs became shared resources. We discuss implications for team-based AI interaction, highlighting opportunities and boundaries for treating AI as a shared resource in collaborative work. Florian Lehmann, Krystsina Shauchenka, Daniel Buschek |
CHI | 2 |