Direct and indirect social robot interactions in a hotel public space
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a study using multiple robots with different socially interactive functionalities in a hotel public space. We analyzed the human attitude toward different styles of interactions with robots, and assessed the use of those robots. We conducted comparative experiments in different settings: (i) Two single robots, Palro and Nao, were used separately to detect the presence of guests and greet them, compared with the same function performed by a hotel-staff. (ii) Twin robots Gemini, as well as dual Naos, engaged in an informative conversation about the hotel, compared with a recorded video of the conversation being displayed on a TV set. In each case, the guest-behavior was studied by using three categories that define the level of a guest's attention. Several statistical significances were found from the results of experiments, which helped to understand the differences between using robot agents and common approaches in the hotel public space.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it