Search Results for author:
Found 12 papers, 5 papers with code
Can Domain Pre-training Help Interdisciplinary Researchers from Data Annotation Poverty? A Case Study of Legal Argument Mining with BERT-based Transformers
Our case study focuses on: the comparison of general pre-training and domain pre-training; the generalisability of different domain pre-trained transformers; and the potential of merging general pre-training with domain pre-training.
A Deep Learning Model for Heterogeneous Dataset Analysis -- Application to Winter Wheat Crop Yield Prediction
We showed that it outperforms the existing ML models.
Enhancing Legal Argument Mining with Domain Pre-training and Neural Networks
In this paper, we provide a broad study of both classic and contextual embedding models and their performance on practical case law from the European Court of Human Rights (ECHR).
UCD-CS at TREC 2021 Incident Streams Track
In recent years, the task of mining important information from social media posts during crises has become a focus of research for the purposes of assisting emergency response (ES).
Crisis Domain Adaptation Using Sequence-to-sequence Transformers
In this paper, we investigate how this prior knowledge can be best leveraged for new crises by examining the extent to which crisis events of a similar type are more suitable for adaptation to new events (cross-domain adaptation).
Transformer-based Multi-task Learning for Disaster Tweet Categorisation
Social media has enabled people to circulate information in a timely fashion, thus motivating people to post messages seeking help during crisis situations.
Multi-task transfer learning for finding actionable information from crisis-related messages on social media
Based on this approach, we submitted several runs to the track.
Assessing the Influencing Factors on the Accuracy of Underage Facial Age Estimation
Swift response to the detection of endangered minors is an ongoing concern for law enforcement.
The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances
This paper describes the UCD system entered for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection.
UCD-CS at W-NUT 2020 Shared Task-3: A Text to Text Approach for COVID-19 Event Extraction on Social Media
The objective of this task is to extract answers from COVID-related tweets to a set of predefined slot-filling questions.
Improving Borderline Adulthood Facial Age Estimation through Ensemble Learning
Achieving high performance for facial age estimation with subjects in the borderline between adulthood and non-adulthood has always been a challenge.
ProbFuse: A Probabilistic Approach to Data Fusion
Data fusion is the combination of the results of independent searches on a document collection into one single output result set.
