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Found 8 papers, 6 papers with code
Are You Misinformed? A Study of Covid-Related Fake News in Bengali on Facebook
The best performing model is BERT, with an F1-score of 0. 97.
CoDesc: A Large Code-Description Parallel Dataset
In this study, we present CoDesc -- a large parallel dataset composed of 4. 2 million Java methods and natural language descriptions.
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BERT2Code: Can Pretrained Language Models be Leveraged for Code Search?
In this work, we leverage the efficacy of these embedding models using a simple, lightweight 2-layer neural network in the task of semantic code search.
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla
In this work, we introduce BanglaBERT, a BERT-based Natural Language Understanding (NLU) model pretrained in Bangla, a widely spoken yet low-resource language in the NLP literature.
Static and Animated 3D Scene Generation from Free-form Text Descriptions
As the choice of words and syntax vary while preparing a textual description, it is challenging for the system to reliably produce a consistently desirable output from different forms of language input.
Early Prediction for Merged vs Abandoned Code Changes in Modern Code Reviews
In our empirical study on the 146, 612 code changes from the three software projects, we find that (1) The new features like reviewer dimensions that are introduced in PredCR are the most informative.
A Benchmark Study of Machine Learning Models for Online Fake News Detection
In this research, we conducted a benchmark study to assess the performance of different applicable machine learning approaches on three different datasets where we accumulated the largest and most diversified one.
