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Record W2287788218 · doi:10.1145/2818346.2823296

Model of Personality-Based, Nonverbal Behavior in Affective Virtual Humanoid Character

2015· article· en· W2287788218 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCharacter (mathematics)Human–computer interactionNonverbal communicationComputer scienceConversationVirtual actorVirtual machinePersonalityVirtual realityPsychologyCommunicationSocial psychology

Abstract

fetched live from OpenAlex

In this demonstration a human user interacts with a virtual humanoid character in real-time. Our goal is to create a character that is perceived as imbued with a distinct personality while responding dynamically to inputs from the environment [4] [1]. A hybrid model that comprises continuous and discrete components, firstly, drives the logical behavior of the virtual character moving through states of the interaction, and secondly, continuously updates of the emotional expressions of the virtual character depending on feedback from interactions with the environment. A Rock-Paper-Scissors game scenario is used as framework for the interaction scenario and provides an easy-to-learn and engaging demo environment with minimum conversation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.254
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations6
Published2015
Admission routes1
Has abstractyes

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