arXiv Machine Learning By Michael Sidorov, Ofer Hadar

Learning QoE from Packet-Level Measurements in Encrypted Video Conferencing Traffic

Read the original on arXiv Machine Learning →

arXiv:2601. 06862v2 Announce Type: replace-cross Abstract: The quality of the user experience has become one of the most important aspects in todays world, as it directly influences individuals willingness to continue using or abandon a product or service.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jul 28

Coordinated Networking for On-Device Agent-Augmented Real-Time Communication

arXiv:2607. 22854v1 Announce Type: new Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents autonomously retrieve, analyze, and generate information in real time to support their interactions.

By Goodsol Lee, Juheon Yi, Jinglu Wang, Haowen Xu, Saewoong Bahk, Yan Lu