Search Results for author:
Found 18 papers, 7 papers with code
Pandemic Literature Search: Finding Information on COVID-19
Finding information related to a pandemic of a novel disease raises new challenges for information seeking and retrieval, as the new information becomes available gradually.
Cross-Domain Language Modeling: An Empirical Investigation
Transformer encoder models exhibit strong performance in single-domain applications.
Combining Shallow and Deep Representations for Text-Pair Classification
Contemporary methods use fine-tuned transformer encoder semantic representations of the classification token in the text-pair sequence from the transformer’s final layer for class prediction.
Towards Panoptic 3D Parsing for Single Image in the Wild
Our proposed panoptic 3D parsing framework points to a promising direction in computer vision.
Query-Focused Extractive Summarisation for Finding Ideal Answers to Biomedical and COVID-19 Questions
For phase B of the BioASQ9b task, the relevant documents and snippets were already included in the test data.
ICDAR 2021 Competition on Historical Map Segmentation
Task~2 consists in segmenting map content from the larger map sheet, and was won by the UWB team using a U-Net-like FCN combined with a binarization method to increase detection edge accuracy.
The Ubiqus English-Inuktitut System for WMT20
This paper describes Ubiqus' submission to the WMT20 English-Inuktitut shared news translation task.
Query Focused Multi-document Summarisation of Biomedical Texts: Macquarie Universiy and the Australian National University at BioASQ8b
This paper presents the participation of Macquarie University and the Australian National University for Task B Phase B of the 2020 BioASQ Challenge (BioASQ8b).
Query Focused Multi-document Summarisation of Biomedical Texts
This paper presents the participation of Macquarie University and the Australian National University for Task B Phase B of the 2020 BioASQ Challenge (BioASQ8b).
Leverage Unlabeled Data for Abstractive Speech Summarization with Self-Supervised Learning and Back-Summarization
In order to build a corpus for this task, it is necessary to obtain the (automatic or manual) transcription of each meeting, and then to segment and align it with the corresponding manual report to produce training examples suitable for training.
Align then Summarize: Automatic Alignment Methods for Summarization Corpus Creation
We report automatic alignment and summarization performances on this corpus and show that automatic alignment is relevant for data annotation since it leads to large improvement of almost +4 on all ROUGE scores on the summarization task.
Searching Scientific Literature for Answers on COVID-19 Questions
Finding answers related to a pandemic of a novel disease raises new challenges for information seeking and retrieval, as the new information becomes available gradually.
ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge
We report on our system for textual inference and question entailment in the medical domain for the ACL BioNLP 2019 Shared Task, MEDIQA.
Question Answering in the Biomedical Domain
Question answering techniques have mainly been investigated in open domains.
OpenNMT: Neural Machine Translation Toolkit
OpenNMT is an open-source toolkit for neural machine translation (NMT).
TED-LIUM 3: twice as much data and corpus repartition for experiments on speaker adaptation
We present the recent development on Automatic Speech Recognition (ASR) systems in comparison with the two previous releases of the TED-LIUM Corpus from 2012 and 2014.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
