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

Jointly Fine-Tuning "BERT-like" Self Supervised Models to Improve Multimodal Speech Emotion Recognition

1 code implementation • 15 Aug 2020 • Shamane Siriwardhana, Andrew Reis, Rivindu Weerasekera, Suranga Nanayakkara

Multimodal emotion recognition from speech is an important area in affective computing.

Jointly Fine-Tuning “BERT-like” Self Supervised Models to Improve Multimodal Speech Emotion Recognition

1 code implementation • Interspeech 2020 • Shamane Siriwardhana, Andrew Reis, Rivindu Weerasekera, Suranga Nanayakkara

Multimodal emotion recognition from speech is an important area in affective computing.

Multimodal Deep Learning Multimodal Emotion Recognition +4

Target Driven Visual Navigation with Hybrid Asynchronous Universal Successor Representations

no code implementations • 27 Nov 2018 • Shamane Siriwardhana, Rivindu Weerasekera, Suranga Nanayakkara

Being able to navigate to a target with minimal supervision and prior knowledge is critical to creating human-like assistive agents.

Navigate Visual Navigation