Admux: An Adaptive Multiplexer for Haptic–Audio–Visual Data Communication
Why this work is in the frame
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Bibliographic record
Abstract
Research trends in multimedia strive to incorporate multiple modalities, such as audio, video, graphics, and haptics, into multimedia applications to enhance the user's experience. Researchers have made significant progress in advanced multimedia by incorporating virtual reality environments, haptics, and scent into the human computer interaction paradigm. However, the communication of multimedia data over the Internet (particularly the haptic media) remains a real challenge since each media has varying and sometimes conflicting communication requirements. This paper proposes Admux, an adaptive application layer multiplexing framework (including a communication protocol) for multimedia applications incorporating haptic, visual, auditory, and scent data for nondedicated networks. Being an application layer framework, Admux is highly adaptable to the application requirements, the media type (haptic, audio, video, etc.), and the network conditions. To facilitate the application-Admux communication, we used haptic application metalanguage descriptions. Second, Admux enhances the network throughput by adopting statistical multiplexing. Finally, Admux enables media prioritization based on the application events and QoS requirements. By simulating an interpersonal teleconferencing system (named the HugMe system), our results showed that Admux provides dynamic bandwidth allocation based on the network conditions, media type, and application events.
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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) | 0.000 | 0.000 |
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.
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