Demo Data from SIGIR 2026 / reviewers in the wild / expert
Kaito Nakamura
dblp:371/3251
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-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 |
Human-robot interaction · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
lifelikeness |
0.9 | 1 | 2025 | Development of Robot Feeding Experience to Improve Lifelikeness · HRI 2025 |
Human-robot interaction › social robot
social robot design |
0.9 | 1 | 2025 | Development of Robot Feeding Experience to Improve Lifelikeness · HRI 2025 |
Methods — techniques the papers use, named apart from their topics
user study · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Development of Robot Feeding Experience to Improve LifelikenessabstractThis study investigated the effect of biomimetic feeding behavior on the perception of lifelikeness in robots. A robot designed to simulate the feeding behavior of the emperor penguin was developed. It features a 3D-printed beak, movable wings, and a furry exterior, which allows for safe tactile interaction. Participants interacted with the robot in two conditions: with and without feeding. The results indicate that feeding may enhance the lifelikeness and perceived intelligence of the robot. This outcome suggests the potential for interaction through feeding to facilitate a deeper connection between humans and robots, which will be useful for designing more lifelike robots in the future. Takuto Akiyoshi, Kaito Nakamura, Taishi Sawabe |
HRI | 2 |