[NAACL 2025] Multi-Agent Legal Simulation Driver (MASER), a synthetic data engine for dynamic legal scenarios.
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Updated
May 29, 2025 - Python
[NAACL 2025] Multi-Agent Legal Simulation Driver (MASER), a synthetic data engine for dynamic legal scenarios.
SeqFlipAttention is a forward‑looking PyTorch demonstration of sequence‑to‑sequence learning enhanced by attention, trained on a synthetic reverse‑sequence task and complete with training scripts, loss and accuracy visualizations, and a quantitative analysis of attention’s impact on performance.
Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. GANs for Synthetic Data Generation leverage deep learning to create realistic synthetic datasets, enhancing AI model training, data augmentation, and performance in scenarios with limited real-world data.
Repo for the Synthetic Data for Machine Learning seminar at IMPA 2021
This repository code file aims to generate random data, which can be assumed of type streaming, in the context of big data, if you connect this source program to a Kinesis Data Stream it becomes Streaming Source.
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