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Found 11 papers, 7 papers with code
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.
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.
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.
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.
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.
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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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.
Enhancing Automated Program Repair through Fine-tuning and Prompt Engineering
We applied PLBART and CodeT5, two state-of-the-art language models that are pre-trained with both PL and NL, on two such natural language-based program repair datasets and found that the pre-trained language models fine-tuned with datasets containing both code review and subsequent code changes notably outperformed each of the previous models.
Contrastive Learning for API Aspect Analysis
For impact analysis, we performed empirical and developer study.
LogShield: A Transformer-based APT Detection System Leveraging Self-Attention
Lately, there have been studies where transformer-based language models are being used to detect various types of attacks from system logs.
