VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research

no code implementations • 6 Jun 2023 • Elliott Wen, Chitralekha Gupta, Prasanth Sasikumar, Mark Billinghurst, James Wilmott, Emily Skow, Arindam Dey, Suranga Nanayakkara

Researchers have used machine learning approaches to identify motion sickness in VR experience.

Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering

1 code implementation • 6 Oct 2022 • Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, Tharindu Kaluarachchi, Rajib Rana, Suranga Nanayakkara

We propose \textit{RAG-end2end}, an extension to RAG, that can adapt to a domain-specific knowledge base by updating all components of the external knowledge base during training.

Domain Adaptation Information Retrieval +3

Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering

1 code implementation • 22 Jun 2021 • Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, Suranga Nanayakkara

In this paper, we illustrate how to fine-tune the entire Retrieval Augment Generation (RAG) architecture in an end-to-end manner.

Open-Domain Question Answering Retrieval

Optimizing Controller Placement for Software-Defined Networks

no code implementations • 14 Feb 2019 • Victoria Huang, Gang Chen, Qiang Fu, Elliott Wen

In comparison to communication delay, existing literature on the CPP assumes that the influence of controller workload distribution on network performance is negligible.