Symbiotic Society with Avatars (SSA): Toward Empowering Social Interactions Beyond Space and Time
Bibliographic record
Abstract
Avatar robots, representations of remote people, help them extend their physical, cognitive, and perceptual capabilities. These avatars can be a range of embodiments from virtual agents to physical robots. With avatar robots, a person (operator) can coexist in multiple locations (beyond space) by controlling multiple avatars simultaneously and move from one place to another without delays (beyond time) by connecting to another avatar in a different location. In the near future, avatar technology would change people's lives dramatically. However, we face various challenges to reach this future, including uncharted knowledge of social interactions between people and avatar robots, missing standardization on developing robots (robot specs and controls), the lack of related laws and ethical rules, and technical difficulties. With this developing area of human-robot interaction, new key challenges and problems, approaches, and data are rapidly emerging. This workshop would act as a key meeting point to focus this effort and discuss avatar robots and related research and form new collaborations to forge ahead toward symbiotic society with avatars.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".