Search Results for author:
Found 9 papers, 6 papers with code
CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language Pairs
LaSE is strongly correlated with ROUGE and, unlike ROUGE, can be reliably measured even in the absence of references in the target language.
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+1
An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers
There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible.
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages
XL-Sum induces competitive results compared to the ones obtained using similar monolingual datasets: we show higher than 11 ROUGE-2 scores on 10 languages we benchmark on, with some of them exceeding 15, as obtained by multilingual training.
TopicTracker: A Platform for Topic Trajectory Identification and Visualisation
Nevertheless, the implementation of the existing methods for topic trajectory identification is rarely available as usable software.
An open-source framework for ExpFinder integrating $N$-gram Vector Space Model and $μ$CO-HITS
Finding experts drives successful collaborations and high-quality product development in academic and research domains.
CorrDetector: A Framework for Structural Corrosion Detection from Drone Images using Ensemble Deep Learning
In this paper, we propose a new technique that applies automated image analysis in the area of structural corrosion monitoring and demonstrate improved efficacy compared to existing approaches.
ExpFinder: An Ensemble Expert Finding Model Integrating $N$-gram Vector Space Model and $μ$CO-HITS
In this paper, we propose $\textit{ExpFinder}$, a new ensemble model for expert finding, that integrates a novel $N$-gram vector space model, denoted as $n$VSM, and a graph-based model, denoted as $\textit{$\mu$CO-HITS}$, that is a proposed variation of the CO-HITS algorithm.
Boosting House Price Predictions using Geo-Spatial Network Embedding
Extensive experiments with a large number of regression techniques show that the embeddings produced by our proposed GSNE technique consistently and significantly improve the performance of the house price prediction task regardless of the downstream regression model.
Keyword Aware Influential Community Search in Large Attributed Graphs
We introduce a novel keyword-aware influential community query KICQ that finds the most influential communities from an attributed graph, where an influential community is defined as a closely connected group of vertices having some dominance over other groups of vertices with the expertise (a set of keywords) matching with the query terms (words or phrases).
